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AI Passport

The EY-Microsoft AI Skills Passport is an introductory program designed to educate participants about Artificial Intelligence (AI) and its impact on various industries. The course covers key concepts such as the definition of AI, its history, and its applications, while also emphasizing the importance of ethical and responsible use of AI. By completing the program, participants will gain a clearer understanding of AI and how to leverage it for future career opportunities.

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0% found this document useful (0 votes)

1K views204 pages

AI Passport

Uploaded by

shronee12

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Available Formats

Download as DOCX, PDF, TXT or read online on Scribd

You are on page 1/ 204

Hey there!

Welcome to the EY-Microsoft AI Skills Passport, your comprehensive introduction

to the vast and exciting world of Artificial Intelligence (AI). You will get to learn all about AI,
and how it impacts key industries.

By the time you've finished the EY-Microsoft AI Skills Passport, you should leave with a much
clearer idea of what AI is, how it's impacting the world, and how you can harness it to unlock
opportunities in your future career!

EY-Microsoft AI Skills Passport: General

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1. Welcome to the EY-Microsoft AI Skills Passport

2. Introduction to AI

This lesson is currently unavailable

Lessons must be completed in order

3. Ethics and responsible use of AI

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Lessons must be completed in order

4. Applications of AI

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Lessons must be completed in order

Home

Welcome to the EY-Microsoft AI Skills Passport

Lesson 1 of 4

Hey there! Welcome to the EY-Microsoft AI Skills Passport, your comprehensive introduction
to the vast and exciting world of Artificial Intelligence (AI). You will get to learn all about AI,
and how it impacts key industries.

Leading the workforce of today is all about empowering the talent of tomorrow. We can do
this by supporting young people and underserved groups from all over the globe to have fair
and equitable access to AI training and skilling programs such as the AI Skills Passport. I
encourage future generations to be curious, upskill themselves on new and emerging
technologies, and to embrace and invent new innovations that will help us all build a better
working world."

- Janet Truncale, EY Global Chair and CEO

EY-Microsoft AI Skills Passport: General

25% COMPLETE

1. Welcome to the EY-Microsoft AI Skills Passport

2. Introduction to AI

3. Ethics and responsible use of AI

This lesson is currently unavailable

Lessons must be completed in order

4. Applications of AI

This lesson is currently unavailable

Lessons must be completed in order

Lesson 1

Introduction to AI

Lesson 2 of 4

Welcome to Lesson 2 of the General module. In this lesson, we'll first look at defining AI and
then determine the differences between what AI can and cannot do. You'll learn about AI's
history and its evolution over time, leading up to present day AI applications and the
everyday AI you might have no idea you're interacting with.

Once you're confident defining AI, you'll get to dive deeper into the workings of AI, exploring
how it becomes 'intelligent'. We'll touch on key concepts and processes in AI such as
Machine Learning, Neural Networks, and Deep Learning, which are all fundamental to the
'Intelligence' of AI. Moreover, you'll get the chance to learn about the people behind AI and
a snapshot of what the future may hold

The question of whether a computer can think is no more interesting than the question of
whether a submarine can swim."

- Edsger Dijkstra, Dutch Computer Scientist

What is Artificial Intelligence?

How do cars drive without a driver? How can a camera recognize your face and distinguish it
from millions of others? How can a machine translate languages with near-human accuracy?
How can a computer generate a photo-realistic image based on what someone has
described?

Welcome to just a small peak at some of the various uses of Artificial Intelligence.

Well, it's partly in the title. 'Intelligence' refers to the ability to learn, adapt, improve, and
perform tasks such as reasoning, problem-solving, comprehending, and decision-making.
The word 'Artificial' refers to the fact that it is man-made.

More broadly, AI is a field of computer science which focuses on creating machine systems
capable of doing things, like problem solving, which would typically require human
intelligence. AI is often categorized into two groups:

1. Narrow AI: Also known as Weak AI, these are systems designed to execute a specific
task, or tasks; for example, an AI trained to master a game of Ches. All present-day AI
models sit under this category.

2. General AI: Also known as strong AI, this is AI that is virtually indistinguishable from
human intelligence - capable of performing any task that requires cognition and
intelligence. At present, this type of AI is purely hypothetical and does not exist,
except maybe in sci-fi movies. Please note - General AI is different from Generative
AI; Generative AI is a form of Narrow AI. We get into more specifics around what
Generative AI is in the next lesson.

In addition, some people agree on a third category, Super AI. This is another hypothetical
form of AI that does not exist but may be able to surpass human intelligence. For this course,
we will mainly be focusing on Narrow and General AI - as Super AI is still a long, long way
away.

Lesson 1

Introduction to AI

Lesson 2 of 4
Welcome to Lesson 2 of the General module. In this lesson, we'll first look at defining AI and
then determine the differences between what AI can and cannot do. You'll learn about AI's
history and its evolution over time, leading up to present day AI applications and the
everyday AI you might have no idea you're interacting with.

The question of whether a computer can think is no more interesting than the question of
whether a submarine can swim."

- Edsger Dijkstra, Dutch Computer Scientist

What is Artificial Intelligence?

Welcome to just a small peak at some of the various uses of Artificial Intelligence.

Video

Watch the short video below by Microsoft, "What is Artificial Intelligence?" (5:09 minutes),
to learn more about what AI is, how it's evolved over time, and what AI may be able to do in
future.

Play Video

Types of AI
Earlier, you learned that AI tends to sit under 2 categories: Narrow AI, and General AI. Let's
take a further look into these AI types and how they work using the tabs below:

Type I: Reactive Machine AI

Type II: Limited Memory AI

Type III: Theory of Mind AI

Type IV: Self Aware AI

Reactive Machine AI are AI models created for very specific tasks, responding to specific
inputs with specific outputs; making this a form of Narrow AI. Reactive AI stores no memory
- meaning they only work with the data available to them, and cannot recall or refer to
previous outputs.

A prominent example of reactive AI includes algorithms as seen in social media and

streaming; these take into account your customer data (such as viewing history and
interactions) to then deliver you recommended viewing that you are likely to enjoy.
Which of the following two options are true statements?

 AI is a form of computer science whereby machines are designed and trained to

replicate human intelligence.

 AI should try to replicate human intelligence as accurately as possible.

 "Intelligence" in "Artificial Intelligence" refers to a computer's ability to seem human

when someone interacts with it.

 Artificial intelligence aims to create machines which can learn, adapt and make
decisions, similar to the way a human does so.

SUBMIT

Correct

That's right!

Match each type of AI with its corresponding description.




 2

Theory of Mind AI

 4

Limited Memory AI

 3

Self-Aware AI

 1

Reactive Machine AI

 AI that can replicate human intelligence and understand human emotions and
reasoning.

 Uses past performance observations to try and improve interactions using present
data.

 AI that is able to recognize itself as a conscious entity with its own needs and wants.

 Responds to specific inputs with specific outputs. Stores no memory.

SUBMIT

Correct

Great job!

Which of the following two options are reasons as to why AI did not progress very quickly
from 1950 - 1990?

 Computers couldn't store information, nor process it very quickly.

 Computers used too much energy to compute even basic AI models.

 There was harsh criticism of AI investment as researchers over-promised AI, but

under-delivered it.
 The public were too concerned around moral and ethical issues of AI.

Lesson 1

Introduction to AI

Lesson 2 of 4

The question of whether a computer can think is no more interesting than the question of
whether a submarine can swim."

- Edsger Dijkstra, Dutch Computer Scientist

What is Artificial Intelligence?

Welcome to just a small peak at some of the various uses of Artificial Intelligence.

Artificial intelligence, or AI, is likely a term you've heard once or twice (or way too many
times). It's a hot topic at the moment, and only seems to be getting more attention every
day. So what is AI, really? And why can it do all these things, like image recognition, or self-
driving cars?
Well, it's partly in the title. 'Intelligence' refers to the ability to learn, adapt, improve, and
perform tasks such as reasoning, problem-solving, comprehending, and decision-making.
The word 'Artificial' refers to the fact that it is man-made.

Video

Watch the short video below by Microsoft, "What is Artificial Intelligence?" (5:09 minutes),
to learn more about what AI is, how it's evolved over time, and what AI may be able to do in
future.

Play Video

Play

Loaded: 100.00%

Remaining Time -5:09

Playback Rate 1x

Picture-in-PictureFullscreen

Mute

Types of AI

Earlier, you learned that AI tends to sit under 2 categories: Narrow AI, and General AI. Let's
take a further look into these AI types and how they work using the tabs below:
Type I: Reactive Machine AI

Type II: Limited Memory AI

Type III: Theory of Mind AI

Type IV: Self Aware AI

A prominent example of reactive AI includes algorithms as seen in social media and

streaming; these take into account your customer data (such as viewing history and
interactions) to then deliver you recommended viewing that you are likely to enjoy.

Let's do a quick knowledge check!

Which of the following two options are true statements?

 AI is a form of computer science whereby machines are designed and trained to

replicate human intelligence.

 AI should try to replicate human intelligence as accurately as possible.

 "Intelligence" in "Artificial Intelligence" refers to a computer's ability to seem human

when someone interacts with it.
 Artificial intelligence aims to create machines which can learn, adapt and make
decisions, similar to the way a human does so.

SUBMIT

Correct

That's right!

Match each type of AI with its corresponding description.

 2

Theory of Mind AI

 4

Limited Memory AI

 3

Self-Aware AI

 1

Reactive Machine AI

 AI that can replicate human intelligence and understand human emotions and
reasoning.

 Uses past performance observations to try and improve interactions using present
data.

 AI that is able to recognize itself as a conscious entity with its own needs and wants.

 Responds to specific inputs with specific outputs. Stores no memory.

1
SUBMIT

Correct

Great job!

Which of the following two options are reasons as to why AI did not progress very quickly
from 1950 - 1990?

 Computers couldn't store information, nor process it very quickly.

 Computers used too much energy to compute even basic AI models.

 There was harsh criticism of AI investment as researchers over-promised AI, but

under-delivered it.

 The public were too concerned around moral and ethical issues of AI.

SUBMIT

Correct

In 1997, the first AI to beat a renowned grand master at Chess was IBM's __________?

Acceptable responses: Deep Blue, Deep blue bot, deep blue, deep blue bot, blue dot

SUBMIT

Correct

How does AI become intelligent?

For many, the emergence of machines that are able to mimic human intelligence can seem
almost like magic! But in reality, this is the result of years of research, development, and
testing. So how can a machine become intelligent?

There are a variety of computer science concepts, methods, and techniques which are used
to create AI, dependent on factors such as the purpose of the AI, availability of data,
complexity of tasks, and more. Regardless of the methods or techniques involved, AI
requires two fundamental things: lots of data and training. Below, we discuss some of the
various techniques used to develop Artificial Intelligence.

Machine Learning

Machine learning (or ML) in computer science uses data and algorithms to imitate human
learning. Over time, machine learning gradually gets better and more accurate, enabling it
to understand patterns in data and adapt to any new data it's introduced to.

Simply put, Machine Learning can be thought of as a way of teaching a computer to make
decisions or predictions by itself. Rather than giving the computer a specific set of
instructions to follow, it's given examples and is trained to recognize patterns.

A common example of AI that uses ML is a recommendation system; services such as movie

or music streaming services use recommendation systems to analyze past behavior and
preferences, so it can recommend movies or music you might like. Similarly, most social
media applications will leverage AI-powered algorithms to recommend new content to you -
for example, the 'For You' page on TikTok will use previous usage data, user interactions, and
viewing data to design a personalized feed with content you would likely want to see.

There are many different types of Machine Learning, which you can learn more about below:
Expert Systems

Most earlier AI models and systems were built using a basic form of machine learning based
on a collection of 'rules' which the AI model would use to determine outcomes. Previously
discussed bots, such as IBM's Deep Blue bot, were such examples. Specifically, these earlier
examples were known as 'Expert Systems'; a collection of rules which assumes human
intelligence can be constructed as a series of "if-then" statements. Here's how it works:

1. "If" (Condition)

Specifies the condition or set of conditions that must be made for a rule to be applicable.
These conditions can apply to input data, the system, or results of other rules being applied.

2. "Then" (Action, or Rule)

Specifies the action to be executed, the rule to be enforced, or the conclusion to be drawn
once the conditions of the "if" clause are met.

3. Knowledge base

The system keeps a knowledge base containing all "if-then" rules which have been
programmed into it. Let's say our Expert System is designed for cooking; in this case, we
could say the knowledge base is like a library of cookbooks with an array of recipes.
4. Inference engine

This is almost the "brain" of the system. The inference engine uses the information stored in
the knowledge base to draw conclusions or infer new information. Using the example of a
cooking Expert System, we can liken the inference engine to being a Master Chef who knows
how to interpret and apply the instructions of recipes to cook up a delicious dish!

To help illustrate how "if-then" rules work, let's use some everyday examples:

 IF my morning alarm has gone off, THEN I get out of bed and turn on the coffee
maker.

 IF the cookies have been in the oven for 12 minutes, THEN check to see if they are
golden brown.

 IF the soil in the garden is dry, THEN water the plants.

 IF I have a cough and a fever, THEN I should see a doctor.

VIDEO
Neural Networks

Neural Networks, also known as Artificial Neuron Networks or Simulated Neural Networks,
are a form of machine learning whereby a set of algorithms are modeled after the human
brain. The emergence of Neural Networks has allowed machines to engage in reinforcement
learning, even being able to perform new tasks that need human intelligence, without
human intervention.

A common example of this type of AI includes facial recognition systems, which use neural
networks to identify and verify individuals based on their facial features.

Simply put, both biological and mechanic neural networks work through basic units called
Neurons, which process and transmit information. Both also learn by forming connections
which strengthen over time and are fantastic at pattern recognition (including recognizing
images, objects, and speech).

Let's see how neural networks work through the "City" example below. Use the interactive
image below to learn more:
Video

Watch the short video below, "How Neural Networks Work" by (opens in a new
tab)Code.org (YouTube, 5:04 minutes) to learn more about Neural Networks through simple
explanations and examples.

https://youtu.be/JrXazCEACVo

DEEP LEARNING

Deep Learning is another subset of Machine Learning, that also uses Neural Networks. In
this case, the Neural Networks are 'layered' so the AI can learn complex patterns with very
large amounts of data.

Deep Learning is particularly suited to tasks like image recognition and understanding
spoken language, which is why it is often used to create Generative AI models - models
which use previous learning to generate new content such as text, images, videos and audio,
based off of a 'prompt' or instructions provided by the user. A prominent example of this
includes DALL-E, which can generate images.
For AI to be able to 'see', deep learning has enabled the creation of Computer Vision - AI
which can extract information from images, videos and other forms of visual media, and
perform actions based on said information.

Natural Language Processing (NLP)

NLP is a form of artificial intelligence that uses Machine Learning specifically to understand,
interpret and generate human language - just as we are able to do when reading, writing,
speaking and listening.

NLP is a subset of computer science that uses machine learning and deep learning along
with computational linguistics (or, in other words, the computational modelling of human
language). The aim of NLP is to enable a computer to be able to understand language to the
extent that it can answer questions, write stories, and even translate languages. ChatGPT
may come to mind as a prominent example of an NLP AI, as "GPT" stands for "Generative
Pretrained Transformer".

There are many different approaches to creating an NLP AI. This can include, but is not
limited to:

Rule-based approaches are used in much earlier forms of NLPs. This involves systems being
built off complex, hand-crafted rules in the form of grammar and dictionaries. This does not
involve machine learning, and so NLPs using rule-based approaches are extremely limited in
their applications.
This method employs statistical analysis to extract and classify elements of language data
(such as text or speech) to predict language patterns, such as identifying commonly co-
occurring words.

Through Deep Learning, these NLP models can capture the complex patterns and nuances of
human language.
Hybrid approaches are a combination of more than one approach, for example using both
rule-based and statistical methods

While there any many different approaches to NLP, many modern-day applications tend to
use some form of machine learning through statistical and/or neural network approaches.
Regardless of the approach, NLP tends to analyze human languages through:

The model may convert sound to text through speech recognition, or if just text, may
simplify it by removing unnecessary elements such as capital letters or punctuation.
The model breaks down sentences into individual phrases or words.

The model analyzes the grammatical structure of sentences, paragraphs and body of text to
determine the role of specific words, nouns, verbs, adjectives, etc.

The model attempts to interpret the context of words and phrases that have multiple
meanings.
The model attempts to determine subjective elements such as emotions and attitudes.

Understanding AI
While we have just defined AI, this doesn't completely illustrate what AI is, and what it is
not. Let's take a further look at this using the tabs below:
AI Predictions and Data Sets

As established, AI algorithms interpret and predict outcomes based on various data inputs
from different sets.

Let's take a look at how AI uses data sets to create different predictions below:

Path Recommendation on a Map

Data Set: Responses rated as helpful in previous customer-chatbot interactions.

Explanation: All previous navigation routes serve as estimators and are updated live with
data from devices that are currently on the route, which uses signals like weather or traffic
congestion.

Key Technology: Internet of Things (devices connected to each other via the internet)

Customer service chatbot

Data set: Historical and live traffic data.

Explanation: This AI is using Reinforcement Learning to understand how to improve the next
conversations and interactions with customers.

Key Technology: Natural Language Processing.

App recognizing plant species

Data set: Images.

Explanation: Neural networks are trained using as many labeled images as possible so it can
recognize related images. The neural networks can then analyze pixels in images to suggest
an answer.

Key Technology: Computer Vision, Neural Networks.

The future of AI

Watch the video below, featuring an AI-generated teacher, to learn about the future
possibilities of AI.
Welcome to Lesson 3 of the General module.

In this lesson you'll learn about what ethics are and why they're important in the
development and deployment of AI. We'll deep dive into how to use AI responsibly, some of
the major concerns and risks of AI, and how to address them. Let's get started!

What is 'Ethics'?

Ethics, in the simplest and most basic terms, is about making choices based on what we
think is right or wrong. It is a prominent branch of philosophy that questions morally what
is good or bad, fair, or unfair.

Ethics is important to everyone; for each of us, we have our own values (what we think is
good), principles (what we think is right), and purpose (what we live for). This forms our
'moral compass', which guides our decisions based on what we individually believe is 'right'
and 'wrong'. For example, consider the following scenarios:

Scenario 1

If you found a lost wallet full of cash, would you keep it, or try to return it to its owner?
Scenario 2

If you made your friend a promise that would negatively impact other people, would it be
okay to break that promise if it meant no one would be negatively impacted?

Scenario 3

Should a lawyer represent someone in court who they deeply believe is guilty - even if they
don't want to - in an effort to give that person a fair trial?

Scenario 4

Is it okay for a student to cheat on a test if it means they will pass an exam that will allow
them to have a better future - e.g. to get admission into a good university?

These ethical dilemmas begin to illustrate the need for ethics, as well as the complexity of
determining what is the 'right' or 'wrong' thing to do.

In AI, it is important that we make sure it is used safely, responsibly, and ethically. Recent
investigations over the years have revealed some of the faults of AI and the negative
implications of these mistakes. As AI continues to evolve and become more integrated in our
lives, researchers, developers, ethicists, and philanthropists alike are driving discussion
around safeguarding AI to minimize any potential harm and maximize its benefits for society

Video

Watch the short video below, "Ethics & AI: Equal Access and Algorithmic Bias" by Code.org
(YouTube, 3:23 minutes) to learn more about the imperative for ethics in AI and its
responsible use.

https://youtu.be/tJQSyzBUAew

Ethical guidelines for AI

Having clear and well-defined ethical and legal guidelines for the development and use of AI
is essential for mitigating any potential ethical risks associated with it. These guidelines aim
to maximize the benefits of AI to people and the planet while minimizing risks.

Generally, ethical guidelines for AI(opens in a new tab) tends to span across the following
domains:
Users and stakeholders should be able to access, view, and understand when and how
they are impacted by AI or when an AI algorithm or model is interacting with them.

AI systems should be fair, inclusive, and accessible. It should not include unfair
discrimination or bias against any individuals or groups.

AI should respect human rights and the autonomy of humans.

AI systems should undergo robust testing, validation, and monitoring to ensure it is reliable
and fit-for-purpose.

Maintain consistent human oversight of AI and intervention capabilities to prevent risks or

negative consequences.

Protect the personal privacy of users and stakeholders though robust governance practices
and data protection measures.
Users and stakeholders should be able to challenge the use or outcomes of an AI system,
particularly if it has impacted said users or stakeholders.

The people responsible for decisions and actions made in the development or maintenance
of AI should be identifiable and accountable for said decisions or actions.

AI should be of benefit to individuals, society, and the environment.

It is important to note that there is no one gold-standard ethics framework being used in the
development of AI - current approaches to developing legislation, regulation and guidelines
varies across jurisdictions, legal systems, and organizations as they attempt to address
challenges separately(opens in a new tab). As AI progresses, there would be great benefit
from international collaboration and regulation, as this could remove over-regulation across
countries, legal complexities, and misunderstandings in what is, and is not, ethical AI.

Using AI Responsibly

Ethical and responsible guidelines for AI aren't just reserved for researchers, creators and
developers of AI. It is equally as important that, as AI users, we utilize AI in ways that are fair,
ethical, and responsible.

While there is also no consistently agreed-upon framework for using AI responsibly, it is

important to consider the following principles:
Embrace responsible AI principles and practices - Training | Microsoft Learn
Ethical concerns of AI

In order to ensure that AI is developed and deployed as ethically and responsibly as possible,
a thorough assessment of the risks of AI needs to be undertaken. With an understanding of
risks, we can then determine how best to address them before they materialize.

Watch this short video, "AI is Dangerous, but Not for the Reasons You Think" (YouTube,
10:18 minutes), which provides a great introduction into why AI ethics are of such vital
importance.
© 2024 TED To learn more about TED, visit TED.com

https://www.youtube.com/watch?v=eXdVDhOGqoE

Risks and concerns of AI

Case Study: Gender Shades Project

Joy Buolamwini - Founder of the Algorithmic Justice League

The Gender Shades Project is a research study initiated in 2016 by Joy Buolamwini (pictured)
- a Canadian - American computer scientist and digital activist - inspired by her own
struggles using face detection systems as a woman of color.

The Gender Shades Project investigated the performance of commercial AI systems, and in
particular, the computer vision task of gender classification (identifying the gender of an
individual based on a photo of them). The findings from this research demonstrated
significant algorithmic bias in major commercially available technologies.

Major tech companies which were evaluated as part of the Gender Shades project went on
to commit, to varying degrees, to stopping the sale of facial recognition and gender
classification technologies.

The publication of the Gender Shades paper has had a major influence on industry
practices, policy and academic research regarding facial recognition technologies, and the
potential harms of AI. This research was heavily featured in Netflix's documentary, Coded
Bias.

After completing the study, Joy Buolamwini founded the Algorithmic Justice League (AJL),
an organization that aims to raise public awareness about the social implications of AI.

Practice Activity

Click the link below to Codecademy's course, 'Navigating AI Ethical Challenges and Risks'.
This course takes less than an hour and gives you the chance to learn more about ethical and
responsible use of AI - including understanding ethical challenges, using ethical decision-
making frameworks and best practices for mitigating ethical risks associated with AI.
Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.

Navigating AI Ethical Challenges and Risks | Codecademy

Case Study: Unethical Uses of AI

Below is a fictional story of the use of AI at a Software Development Company.

Please read the case study and answer the questions below.

The AI Recruitment Scandal at Codex Solutions

Codex, a prominent software development company, decided to implement an AI-driven

recruitment system to streamline its hiring process.

The AI was designed to scan resumes and shortlist candidates based on keywords,
experience, and education, with the goal of automating a task that the human resources
(HR) team previously did. With this, the HR team could now focus more on other tasks like
interviewing candidates, while ensuring a high quality, small pool of candidates from the
original - much larger - group of applicants.

Codex also implemented facial recognition technology to use during video interviews, to
analyze candidates' expressions and body language, assigning scores on the persons' ability
to display and regulate emotions; this impacted their chances of being hired.

For the whole interview process, none of this AI technology was disclosed to
candidates. Many months later, the HR team had learned that the AI scanning resumes was
actually extremely biased; the pool of candidates as a result of their resume-scanning AI
gave them a pool of similar people predominately male, Caucasian, and from prestigious
universities.

A recent candidate who was unknowingly exposed to facial recognition AI learned about the
use of these technologies in their own interview process. After researching the company
policies, they found that there was nothing to safeguard against bias; moreover, after
researching the company that created the facial recognition technologies, they found that it
had disproportionately affected candidates who were nervous or had atypical expressions
due to cultural differences or neurodiversity.
In the last three lessons, you've learned about what AI is, its history and how it becomes
intelligent; you've also learned about the importance of ethics and using AI responsibly.

In this lesson, you will learn about the use cases and applications of AI, and the many ways it
could potentially be used across a variety of industries and domains. You'll also get the
chance to jump into some common AI models available today and practice using them. Let's
get started!
Applications of AI
Use the flashcard below to understand general uses of AI in any field.

Ingest new information to provide AI services tailored to the issue or industry. E.g. To scan
agricultural areas to make decisions about what farming needs to be done.

Automate activities with bots built with Power Virtual Agents. E.g. You can automate
submission of timesheets or leave with Power Virtual Agents.

Classify text(s) using sentiment analysis. E.g. Can organize customer reviews by positive,
negative, or neutral.

Generate high-quality written content. E.g. Write articles, blog posts, and memoranda.

Extract and compare key terms in emails, text, and contracts. E.g. Identifying and analyzing
specific pieces of information that are critical to the understanding and interpretation of the
content.
Train models on proprietary data and content to provide answers in natural language. E.g.
Improve customer chatbot by preprepared answers and training with natural language.

Summarize lengthy texts to shorter versions. E.g. emails, lengthy documents, or published
laws.

Translate documents from English to other language and vice versa. E.g. translating web
pages, reports, documents, emails.

Case Studies: AI for Social Good

AI for social good refers to the application of AI to address and solve societal challenges.
There are a wide range of organizations, projects and initiatives using AI for positive social
impact, so let's take a look!

START

Case Study 1

Apollo Agriculture, Kenya: Using AI for Personalized Farming

Apollo Agriculture addresses food security in Kenya, and wanted to automate agricultural
information for small-scale farmers. Using an AI system that provides tailored, customized

recommendations, Apollo helped small-scale farmers to improve profitability and

productivity of their farm.

Case Study 2

Wuqu' Kawoq, Guatemala: AI for Neonatal Survival

In Guatamala, a range of barriers (such as language, finances and distance) prevent native
Maya women from receiving essential care during pregnancy and birth. Wuqu' Kawoq's AI
toolkit empowers Guatemalan midwives to identify birth complications swiftly, enhancing
neonatal survival. Developed by healthware professionals in collaboarion with traditional
Mayan midwives, this innovative solution bridges traditional practices, culture and language
with modern technology, offering real-time support to enhance neonatal healthcare in
remote communities.

Case Study 3

Hagdarshak, India: AI-Assisted Access to Welfare

Haqdarshak wanted to simplify the complex bureaucratic procedures associated with

obtaining welfare assistance, to make it easier for rural populations to access benefits. Using
an AI chatbot that provides real-time assistance and guidance, users were able to receive
essential support - improving their quality of life and financial wellbeing.
Using Generative AI

Generative AI might just be one of the most broadly applicable AIs out there. As a reminder,
you learned in Lesson 1 that generative AI (GenAI) is any AI that can create content - like
images, videos, text, and audio.

When using GenAI, we need to know how to best interact with it to give us the outputs we
want. This is known as prompt engineering; whereby you optimize your inputs (instructions)
to get the outputs you want. Prompts can come in the form of instructions (such as "make
up a recipe for X" or "summarize the key findings from X research), or questions (such as
"why did X happen?" or "what does X mean?").

There are several different common approaches to prompt engineering:

Giving a direct and simple prompt without providing additional information. This is best for
simple tasks. For example: "Create a picture of a cute cat".

Providing a prompt with examples to help guide the outputs of the AI. This is suitable for
relatively simple tasks. For example: "Give me some common slang words used in Australia.
For example, 'servo', 'arvo' and 'parmi'".
This improves the output of the AI by providing it with more context and guidance - leading
it through the 'thinking' you want it to do. This is better suited to more complex tasks.

Non-COT: If you have 2 oranges and you buy 4 more, how many oranges do you have in
total?

COT: 1. Start with the number of oranges you already have, which is 2. 2. Add the number of
oranges you bought, which is 4. 3. Calculate the total: 2 + 4 = 6 oranges. 4. The answer is
that you have 6 oranges in total.

This splits complex tasks into smaller steps, whereby each subsequent prompt builds upon
the response from the previous one.

Prompt Response

Help me come up with

Sure! How about a 1920s
1 a theme for my 21st
theme?
birthday party

For a 1920s party,

I like the idea of a consider decorations like
1920s party! What art deco backdrops, gold
2
decorations should I and black balloons,
buy? beaded curtains and
vintage posters!
Those decorations You can find some 1920s
sound great! Where decorations at dollar
3 can I find these stores, department
decorations on a stores, party supply
budget? stores or online.

Structuring Prompts

To better understand prompts, let's take a look at the structure of an effective prompt.
Be clear

Make sure your instructions include enough detail and are clear in what you are requesting.
For example, you could say "give me a recipe for cookies" or "give me a recipe for chocolate
chip cookies using simple ingredients I might have around the house". The latter prompt is
much clearer and less vague.

Use variations

GenAI can iterate outputs based on your inputs. Experiment with the ways you write your
inputs (prompts) to see how this changes the outputs you're getting.

Include follow-ups

Ask further questions, or provide further instructions to better refine your outputs.

Use different techniques

Depending on the complexity of the task, you can use different prompting techniques like
the ones explained above.
Practice activity

Click the link below to Codecademy's course, 'Differentiate for Language and Reading Level
with Generative AI Case Study'. This course takes less than an hour and gives you the
opportunity to practice prompt engineering with ChatGPT.

Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.

Differentiate for Language and Reading Level With Generative AI Case Study | Codecademy
Why soft skills matter | LinkedIn Learning
Welcome to the EY-Microsoft AI Skills Passport Sustainability deep dive! In this section, you
will be introduced to the world of sustainability, and the many ways AI is changing the
various fields and subsectors of sustainability.
Welcome to Lesson 2 of the Sustainability deep dive.

In this lesson, you will gain an overview of the sustainability sector and green jobs which
contribute to social and environmental good. You'll get the chance to engage further with a
learning activity that provides a deep dive into green jobs and career paths. Let's get
started!

What is the Sustainability Sector?

Sustainability is a broad field encompassing all industries, organizations and initiatives

which aim to protect and conserve natural resources. This involves efforts to reduce the
impact of human activities on the environment, while also working to create sustainable
development that ensures responsible use of natural resources.
The Sustainable Development Goals (SDGs)

In 2015, the United Nations (UN) proposed 17 goals for sustainable development, known as
the SDGs, which were adopted by all UN Member states. These goals were developed in
recognition that humanitarian challenges (such as poverty, inequitable access to education
and healthcare) go hand-in-hand with environmental challenges, and that peace and
prosperity can only be achieved through a holistic view of all challenges facing people and
the planet.

These goals have set a consistent global standard of the objectives of the Sustainability
sector and recognize that progress in one area will impact outcomes in others. These goals
sit within areas of environmental conservation, climate change mitigation, social equity,
economic growth, education, gender equality, corporate responsibility and more.
Video

Watch the short video below, "Do you know all 17 SDGs?" by the United Nations (YouTube,
1:25 min) to learn about the Sustainable Development Goals and what they are.

Do you know all 17 SDGs?

Green Jobs and the Green Economy

Green Jobs are the popular term used to describe employment which contributes to
sustainability in areas of environment, society and the economy. Green jobs are considered
an essential facet of the global transition to net-zero emissions, as these jobs will be
responsible for enacting sustainable change.

Much like green jobs, the green economy refers to an economic system that aims to reduce
environmental damage through sustainable development, where the use and consumption
of natural resources do not exceed what the Earth can naturally supply.

In the sustainability field, the terms 'Blue Jobs' and 'Blue Economy' are also used - referring
to the sustainable use of resources derived from the oceans, seas and coasts - advocating
for the protection of the marine environment, which is just as important as protecting our
land environments.

What Kind of Work Can You Do with a Green Job?

As explained, the sustainability sector is a very large field encompassing a range of

industries, institutions and organizations. While we have attempted to list some common
areas and roles below, it's extremely difficult to list everything - there's so much you can do!

See below a snapshot of some of the examples of work you could do in the Sustainability
field:
 Biologist or Microbiologist

 Climate Scientist

 Natural Resources Manager

 Environmental Health and Safety Officer

 Energy Auditor

 Wind Turbine Technician

 Energy Consultant

 Solar Installer

 Ecologist

 Organic Farmer

 Park Ranger

 Agronomist

 Recycling Coordinator

 Wastewater Treatment Engineer

 Waste Reduction Specialist

 Environmental Waste Auditor

 Human Rights Advocate

 Equality and Diversity Campaigner

 Human Rights Journalist

 Humanitarian Aid Worker

 Urban Planner

 Green Infrastructure Engineer

 Transportation Analyst

 Sustainable Community Developer

 Environmental Lawyer

 Sustainable Policy Officer

 Environmental Lobbyist

 Corporate Sustainability Coordinator

 Sustainability Analyst

 Environmental Economist

 Sustainable Finance Analyst

 Carbon Pricing Specialist

 Marine Biologist

 Coastal or Marine Park Ranger

 Ocean Policy Analyst or Lawyer

 Coastal Restoration Specialist

 Video
 Watch the short video linked below, 'What is a Green Job?'
(3:45 minutes) on LinkedIn Learning.
https://www.linkedin.com/learning/green-jobs-for-sustainable-careers/what-is-a-green-job
Key Points

1. 1

The sustainability sector is built on three core pillars: Environmental sustainability

(conservation and protection of natural resources), Social sustainability (ensuring societal
equality and peace), and Economic sustainability (sustained growth and development
without depleting natural resources).

2. 2

The United Nations has established 17 SDGs that provide a global framework for addressing
complex sustainability challenges, ranging from environmental conservation to social equity
and economic growth.

3. 3

Green jobs contribute to sustainability across various sectors, including environmental

conservation, energy transition, agriculture, and more. These jobs are crucial for the
transition to a net-zero emissions economy and are part of the broader green economy,
which aims to minimize environmental damage and promote sustainable development.

Welcome to Lesson 3 of the Sustainability deep dive.

In this lesson we focus on the link between AI and sustainability, exploring the
transformative role of AI in addressing climate change and contributing to the UN
Sustainable Development Goals. You'll learn about AI's capabilities in environmental analysis,
resource optimization, and energy management. The lesson also covers AI's impact on social
and economic sustainability, improving access to services, workforce planning, and policy-
making. Additionally, you'll examine the ethical considerations of AI deployment, including
risks to the environment, society, and economy. The deep dive emphasizes the principles of
AI for Social Good and includes case studies that showcase AI's positive influence on
sustainability efforts.
Video

Watch the short video below, "Can AI Help Solve the Climate Crisis?" by Sims Witherspoon
(YouTube, 12:16 minutes) to introduce you to the ways AI could be used to address the
climate crisis.
© 2024 TED To learn more about TED, visit TED.com(opens in a new tab)

Can AI Help Solve the Climate Crisis? | Sims Witherspoon | TED

What Can AI Do for the Future of Sustainability?

Technovation
Technovation is a global education non-profit that empowers girls to develop their skills in
Tech - as leaders and creatives. Technovation’s mentorship approach has enabled thousands
of young girls to develop innovative apps that address some of the most pressing issues in
their communities. For example, in India, the Quake it Off app uses machine learning and AI
to provide live and future earthquake predictions for the user’s location. The app's machine
learning model is trained on earthquake catalog data, while the app uses AI to generate the
safest evacuation routes for users. In Lamu, Kenya, the Usafiri app uses data from various
websites to detect and alert fishermen of an incoming high tide. This helps prevent marine
fatalities within the island community, of which there were 166 in 2021. These are just a few
examples of innovative solutions being developed by girls receiving mentorship through
Technovation.

You can learn more about Technovation by visiting their website(opens in a new tab).

EY-Microsoft Space for Earth

EY-Microsoft Space for Earth is a tool that leverages satellite data and AI to help
organizations enhance their performance and innovation. By integrating Earth observation
data with Machine Learning, the tool can be used to improve climate resilience and
emissions monitoring. The tool can be applied to a range of industries and applications,
such as water resources, power and utilities, transport and logistics, and more.

You can learn more about EY-Microsoft's Space for Earth Platform here(opens in a new
tab). You can also download the EY-Microsoft Space for Earth app here(opens in a new
tab).
Smart Cities

Smart cities are urban areas that leverage digital technology, particularly the Internet of
Things (IoT) and AI, to collect data and efficiently manage assets, resources, and services.
These cities prioritize green practices and renewable energy, bolstering sustainability.

Smart cities integrate sensors and AI to enhance urban efficiency and sustainability; they can
monitor traffic, air quality, and energy, optimizing resources and reducing environmental
impact. Technologies such as adaptive traffic lights and smart grids improve energy flow and
efficiency. Digital platforms also improve city governance by connecting residents with city
officials. Overall, smart cities represent a convergence of technology, infrastructure, and data
to create more efficient, sustainable, and livable urban spaces for the future.

You can learn more about Smart Cities by listening to this episode(opens in a new
tab) from BBC's Podcast Thinking Allowed.

Learning Activity

Complete the external e-learning below, "An Introduction to AI and Sustainability" on

LinkedIn Learning.

In this course, you will learn about the intersections of AI and sustainability, and ways AI is
becoming a game-changer in progressing sustainability initiatives.

Please watch all videos from the following sections:

 Introduction

 1. What Does AI Have to Do with Sustainability

 2. AI is a Critical Game-Changer for Sustainability

You shouldn't need to sign in to view the videos in this course. This activity will take
approximately 25 minutes to complete, but you can go at your own pace!

https://www.linkedin.com/learning/an-introduction-to-ai-and-sustainability
Risks and Concerns for AI on Sustainability

Watch the video below, featuring an AI-generated teacher, to learn about some of the risks
and concerns surrounding AI and it's potential implications for sustainability.
Using AI for Social Good

In the General Learning section, we discussed some of the principles for ethical AI. While
this is important, and addresses ethical issues, this doesn't entirely recognize the SDGs.
More recently, numerous organizations, businesses and start-ups have begun to focus on
ways of building AI to address the SDGs, known as AI for Social Good (AI4SG); emerging
from this, organizations have attempted to develop consistent guidelines and language for
AI4SG.

A recent study published in Nature(opens in a new tab) analyzed the various AI for Social
Good (AI4SG) guidelines published by a range of institutions such as the UN(opens in a new
tab) and OECD(opens in a new tab). In addition to facilitated collaboration with various
domain experts, the researchers developed the following guidelines for AI4SG:
These guidelines, while aimed at benefitting non-governmental organizations (NGOs), are
applicable to a range of different types of organizations.
Case studies: World Bee Project

Let's deep dive into one way in which AI is being used for good: the World Bee Project
OUTCOMES
Key Points

1. 1

AI has the potential to address climate change and contribute to the UN Sustainable
Development Goals by analyzing environmental data, optimizing resource use, and
managing energy more efficiently.

2. 2

While AI offers many benefits for sustainability, it also poses risks such as environmental
impact due to its energy consumption, potential to exacerbate social issues through bias,
and economic implications. Responsible AI development and deployment are crucial to
mitigate these risks.

3. 3

The concept of AI for Social Good (AI4SG) focuses on using AI to address the Sustainable
Development Goals, with guidelines emphasizing grounded expectations, simplicity,
inclusivity, ethics, and data security to ensure AI's positive impact on society.
Welcome to Lesson 4 of the Sustainability deep dive.

In this lesson, you'll delve into the synergy between AI and sustainability-focused careers.
The content highlights AI's potential to revolutionize green jobs by enhancing data analysis,
automating routine tasks, and fostering innovative solutions to environmental challenges.
You'll learn about the essential skills needed for these roles, ranging from technical expertise
in environmental sciences to soft skills for effective collaboration. The lesson also
emphasizes the benefits of AI proficiency in green jobs, such as improved productivity and
decision-making. Additionally, it explores emerging career paths at the AI-sustainability
nexus, underscoring the growing demand for talent equipped with AI and digital skills in the
green economy.

How can AI be Used in Green Jobs?

AI has many use cases across different areas of sustainability, addressing some of the biggest
challenges we face as a society.

AI can also enhance how we work in our professional lives and in green jobs, AI presents an
attractive tool which can improve the quality of our work, how we work, and where we
direct our energy.

AI can be applied across many different aspects of a green job - from the way we analyze
data, to the way we innovate solutions - and can improve productivity. While AI's potential
to be of benefit to a particular job is dependent on the nature of said job, AI can generally be
used in Green Jobs to:
AI can analyze more data much faster than human researchers, identifying patterns and
trends in vast datasets with very little time. In some cases, AI can do this better than
humans, picking up on trends otherwise overlooked. This can help individuals to make better
informed decisions, much quicker.

AI can automate simple, repetitive, or tedious tasks. For someone working a green job, AI
might be used to automate data entry or report generation. This allows the individual more
time to focus on more creative or complex work.

AI-powered tools can be used to facilitate better communication and collaboration across
team members and stakeholders. Tools such as GenAI models can improve the way we
express information, and with a few small prompts, can do it much faster.

AI can help us to understand our current skills and knowledge, and where skills are present,
based on the current trends and demands of the workforce. For someone working a green
job in today's ever-changing environment, this can help someone adapt and stay ahead of
in-demand skills.

AI can be used to help us understand the current state of something, but also the potential
implications of change. AI can be used for predictive analysis or scenarios, allowing us to
experiment with the effects of something. For example, this would be an extremely helpful
tool for someone implementing a new policy, to see how this could impact the environment,
society or the economy.
AI can help us identify opportunities or solutions to challenges. This could be extremely
helpful for individuals in green jobs who are working to address complex sustainability issues
or challenges.

Skills Needed to Land a Green Job

Every job we encounter will have a requirement for a particular set of skills, knowledge and
experience. For instance:

1. 1

How could you work as a chef if you didn't know how to use a knife or oven?

2. 2

How could you work in customer service if you didn't know how to talk to people?

3. 3

How could you be a bus driver if you didn't know how to drive?
What Skills do I need for a Job in Sustainability?

The variety of work you can do in the sustainability sector are vast and diverse - from
environmental science to humanitarian work, to economics and business. Let's take a look at
some of the key skills required in a range of typical green jobs!

Typical skills include:

 Understanding of natural sciences, such as Biology and Ecology

 Ability to conduct fieldwork, collect samples and conduct surveys

 Understanding of local legislation, policies and regulations regarding environmental

management

 Ability to analyze and draw insights from environmental data

 Critical thinking and problem solving to address complex conservation challenges

 Effective communication skills and the ability to collaborate with others

 Ability to write reports and educational materials

Jobs in the energy transition can range from technical engineering roles to sales
management and health and safety roles. Some of the desired skills include:

 Technical understanding of energy technologies, storage and energy efficiency

measures

 Ability to design and engineer energy systems (required in specialized technical roles
such as Electrical Engineers)

 Ability to draw insights from energy data

 Understanding of contract management and sales expertise

 Understanding of the legislation, policies and regulations that govern the local
energy industry
1. Typical skills include:

 Understanding of sustainable farming practices and organic agriculture

 Familiarity with soil science, water conservation, reforestation and

remediation practices

 Ability to plan, implement and manage agricultural projects

 Ability to conduct research and take samples

 Understanding of agricultural policies and legislation

Typical skills include:

 Understanding of sustainable farming practices and organic agriculture

 Familiarity with soil science, water conservation, reforestation and remediation

practices

 Ability to plan, implement and manage agricultural projects

 Ability to conduct research and take samples

 Understanding of agricultural policies and legislation

Typical skills include:

 Understanding of sustainable urban design principles and land use planning

 Understanding of sustainable development practices, including sustainable materials

and construction methods
 Knowledge of laws and policies surrounding construction (such as building codes and
zoning laws)

 Ability to use Coputer-Aided Design (CAD) software to create and interpret

architectural plans

 Familiarity with green building certifications such as LEED

Typical skills include:

 Thorough understanding of local/national and even global laws and policies

 Excellent written and verbal communication skills

 Ability to speak and present to others in public forums

 Ability to network and form relationships, establishing connections with key decision-
makers

 Can design and implement various campaigns to influence public opinion and policy
decisions

 Understanding of legislative processes and the process behind the creation of policy

Typical skills include:

 Thorough understanding of international human rights law and conventions

 Familiarity with domestic laws and legal systems relating to civil rights, anti-
discrimination and equality

 Ability to research and present data to support advocacy and policy work

 Ability to gather public support through campaigns, petitions and other forms of
advocacy

 Excellent written and verbal communication skills

 Understanding of cultural differences and the ability to work in multicultural

environments
Typical skills include:

 Thorough understanding of economics and the mechanisms through which the

economy operates

 Understanding of sustainable development principles and practices

 Proficiency collecting and drawing insights from data, for the purposes of - for
example, environmental impact assessments, energy auditing and emissions
disclosures

 Ability to plan and implement projects

 Knowledge of laws and policies relating to environment and human rights

 Creative thinking and ability to develop effective business strategies for sustainable
operations

 Excellent communication skills; in particular, the ability to discuss data insights to a

range of audiences

 Ability to collaborate with a diverse range of professionals - from environmental

scientists, to policy makers, to human rights activists

 Learning Activity
 Complete the external e-learning below, "Closing the Green Skills
Gap to Power a Greener Economy and Drive Sustainability"
on LinkedIn Learning.

 In this course, you'll learn about the ways that the world of work is
adapting to the green economy, what green skills are, and what the
future of green skills might look like.

 Please watch all videos from all sections of the course.

 You shouldn't need to sign in to view the videos in this course. This
activity will take approximately 20 minutes to complete, but you can
go at your own pace!
Skills we need to make our future green | LinkedIn Learning
AI Skills for Green Jobs

As AI technology continues to progress, and more organizations adopt AI to leverage its

benefits, having AI skills in any job is becoming more and more valuable. Moreover, it is
incredibly clear that AI and sustainability can work hand in hand; having AI skills in a
sustainability-focused job would allow you to thrive, while advancing your capabilities in
your role. Let's take a look at some AI skills that would be advantageous in green jobs:

Being able to develop and deploy models that can help forecast environmental changes,
optimize resource use, and assess the impact of sustainability initiatives.

Using NLP, you can analyze and process unstructured linguistic data. In sustainability, this can
be used to monitor public sentiment on environmental issues, analyze policy documents, or
extract information from research papers.

Using AI to analyze and interpret visual data. In sustainability, computer vision can be used
for monitoring wildlife, assessing deforestation, detecting pollution, and managing waste.
The ability to develop algorithms which can be used to optimize processes. Optimization is
key in reducing waste, improving efficiency, and minimizing environmental impact in various
industries.

Having an understanding of how to build and deploy AI models with minimal environmental
or social impact. Developing sustainable, ethical AI models and systems aligns with
sustainability goals by reducing the carbon footprint of AI technologies while avoiding biases
and ensuring fairness.

Being able to automate processes using AI. Automation can enhance efficiency, reduce
manual labor, and expand the reach and impact of sustainability efforts.

Integrating AI with GIS can enhance spatial analysis, which is critical for land use planning,
monitoring environmental changes, and managing natural resources.

The ability to design AI systems that can support decision-making processes. AI can provide
data-driven insights to guide policy-making, resource management, and corporate
sustainability strategies.
The ability to communicate AI systems and AI insights to non-technical stakeholders (i.e.,
people without technical knowledge of how AI works or what it is). Sustainability projects
often involve collaboration between scientists, engineers, policymakers, and business
leaders, making effective communication essential.

Benefits of AI Skills for Green Jobs

Watch the video below, featuring an AI-generated teacher, to learn about the benefits of
having AI skills in a green job.
Having AI skills in green jobs enables many more benefits to those listed above. Overall, AI
and digital skills are in high demand and are still on the rise; more employers are seeking
candidates with these skills, as sustainability experts who bring AI skills enable organizations
to reap the potential rewards of adopting AI.
Key Points

1. 1

AI can significantly improve green jobs by automating tasks, enhancing data analysis, and
fostering innovation to address environmental challenges.

2. 2

A combination of hard skills (like environmental science and AI technology) and soft skills
(such as collaboration and communication) are crucial for success in green jobs.

3. 3

Proficiency in AI can provide a competitive edge in the green job market, enhancing
productivity, decision-making, and cross-disciplinary collaboration in sustainability efforts.

Congratulations!

You have reached the end of the AI and Sustainability deep dive. Next, you will explore the
Business and Entrepreneurship and Technology deep dives. Then, you will complete an
Employability module to finish the course and receive your certificate of completion!
Welcome to the Industry Deep dive - Exploring AI Skills in Business and Entrepreneurship.

This deep dive will introduce you to principles of business, commerce and entrepreneurship
and how AI is being used in the public, private, and government sector.

This deep dive will conclude with guidance and resources for further education, job-
searching, and finding employment within the Business and Entrepreneurship sector, with
relevance for using or creating AI.

Welcome to the Business and Entrepreneurship Deep Dive

2. Introduction to Business and Entrepreneurship

This lesson is currently unavailable

Lessons must be completed in order

3. AI and Business
Watch the video below, featuring an AI-generated teacher, to welcome you to the Business
and Entrepreneurship deep dive.

Welcome to Lesson 2 of the Business and Entrepreneurship deep dive.

In this lesson you will learn about how AI is being embraced by all different types of
businesses, small to large, across industries and sectors. You’ll have a better understanding
of the various roles within a business, and how they are being augmented with the efficient
use of AI. Moreover, we will examine the intricate connections between business
enterprises, economic frameworks, and governmental policies - emphasizing the pivotal role
of businesses in fostering innovation. Finally, we'll take a look at how entrepreneurs are
using Artificial Intelligence to advance their endeavors. Let's get started!

What is a Business?

Think of a business as a player in the grand game of the economy. It's like a living, breathing
thing that's set up to make and sell stuff—whether that's the latest tech gadget, a mind-
blowing espresso, or a service that makes life easier, like an app that organizes your social
life or a gym that keeps you fit.

A business can be a solo mission or a global empire with thousands of employees. The aim?
Usually, it's to make some cash, but it's also about filling a gap in the market — solving a
problem or offering something better, faster, or cooler than what's out there. And in doing
so, it creates jobs, shapes trends, and sometimes even changes the world.

Businesses can have a variety of different functions, depending on the size, which include:

Responsible for selling products or services to customers and generating revenue. Sales
strategies, customer relationships, and meeting sales targets are key aspects of this
function.

Focuses on promoting the company's products or services to the target audience. This
includes market research, advertising, public relations, and product development.
Manages the company's financial health, including accounting, budgeting, forecasting, and
investment strategies. The finance department also prepares financial statements and
ensures compliance with financial regulations.

Handles recruitment, training, employee relations, benefits, compensation, and compliance

with labor laws. HR also works on maintaining a productive and positive work environment.

Oversees the day-to-day activities that contribute to the production of goods or services.
This includes supply chain management, inventory control, quality assurance, and process
improvement.

Manages the company's technology infrastructure, including hardware, software, data

management, and cybersecurity. IT supports other functions by providing the necessary
technological tools and systems.

Ensures customer satisfaction by addressing inquiries, resolving issues, and providing

support. This function is crucial for maintaining a positive relationship with customers and
encouraging repeat business.

Responsible for sourcing and purchasing goods and services that the company needs to
operate. This includes negotiating with suppliers and managing contracts.
Handles all legal matters, including contracts, intellectual property, compliance with laws
and regulations, and litigation. The legal department advises the company on legal rights
and obligations.

Video

Watch the short video below, "Introduction to Entrepreneurship Essentials" by Harvard

Business School Online (YouTube, 2:10 minutes) to learn more about entrepreneurship skills.

Introduction to Entrepreneurship Essentials

What is Entrepreneurship?

Case Study: Bill Drayton - Pioneering Social Entrepreneurship

Background

Bill Drayton, often recognized as the father of social entrepreneurship, has a rich background
in innovation and public service. With a degree from Harvard and a stint as a management
consultant, Drayton was well-versed in the mechanics of business and the power of systemic
change

The Spark

Drayton's entrepreneurial journey began with his deep-seated belief in the importance of
societal improvement. He was particularly interested in finding solutions to social issues
through business-like strategies. His work as an Assistant Administrator at the Environmental
Protection Agency (EPA), and his experiences traveling the world, exposed him to various
social challenges and the potential for innovative solutions.

The Launch

In 1980, Drayton founded Ashoka: Innovators for the Public, a global organization that
identifies and supports leading social entrepreneurs. The name "Ashoka" was inspired by an
ancient Indian emperor who worked to spread social welfare. Drayton's vision was to build a
community of change-makers who could independently develop solutions to social problems
and drive systemic change.

The Growth

Ashoka grew exponentially under Drayton's leadership. It has supported over 3,500 social
entrepreneurs in more than 90 countries, tackling issues from education and health to
environmental sustainability and women's rights. Drayton's model emphasizes the
importance of collaboration, empathy, and creativity in addressing complex social issues

The Entrepreneurial Traits

Drayton's entrepreneurial spirit is marked by his innovative approach to social change, his
strategic thinking, and his ability to inspire and mobilize a global network of change-makers.
He saw entrepreneurship not just as a means to create businesses, but as a tool to empower
individuals and transform societies.

Summary

Bill Drayton's entrepreneurial journey is a testament to the power of social innovation. By

fostering a global network of social entrepreneurs, Drayton has demonstrated that with the
right support and community, individuals can create sustainable impact and drive progress
across the world. His work with Ashoka continues to inspire new generations of
entrepreneurs to view business as a platform for positive social change.

The Importance of Business Acumen and Entrepreneurial Skills

Watch the video below, featuring an AI-generated teacher, to learn about the importance of
business acumen and entrepreneurial skills.
Learning Activity

Complete the learning below, "Developing Business Acumen" by LinkedIn (1:07 hrs.) to
learn more about ways of developing key business skills.

Developing Business Acumen (2016) | LinkedIn Learning

The Interplay of Business, Economy, and Entrepreneurship

Video

Watch the short video below, "Social Innovation" by Dr Jeff Snell (YouTube, 19:48 minutes)
to learn more about the importance of social innovation in business.
© 2024 TED To learn more about TED, visit TED.com

Social Innovation | Jeff Snell | TEDxUWMadison

Business Economics

As an aspiring entrepreneur, understanding basic economics and managing business cycles

are crucial to navigating the complexities of running a business. Here are some key concepts
you'll need to grasp:

Supply and Demand

This fundamental economic principle dictates how prices are set in a market. Supply refers
to how much of a product or service is available, while demand is how much consumers
want it. When demand exceeds supply, prices tend to rise, and when supply exceeds
demand, prices usually fall. Entrepreneurs must understand this dynamic to price their
products or services effectively.

Costs and Revenue

To run a profitable business, you need to know your costs (both fixed and variable) and how
they relate to your revenue. Fixed costs remain the same regardless of how much you
produce, like rent and salaries. Variable costs change with production levels, like materials
and labor. Revenue minus costs equals profit, the ultimate goal for sustainability and growth.
Cash Flow Management

Cash flow is the heart of your business. It's the net amount of cash moving in and out of
your business at any given time. Positive cash flow means you have more money coming in
than going out, which is essential for covering expenses, investing in growth, and preparing
for lean times.

Business Cycles

The economy goes through cycles of growth (expansion) and contraction (recession). During
expansion, consumer spending increases, leading to higher demand for products and
services. In a recession, spending decreases, and demand drops. Entrepreneurs must be able
to adapt their strategies to these cycles, such as managing inventory levels, adjusting
marketing strategies, and securing financing to weather downturns.

Market Trends and Consumer Behavior

Keeping an eye on market trends and understanding consumer behavior can help you
anticipate changes in demand for your products or services. This foresight can inform
product development, marketing efforts, and overall business strategy.

Interest Rates and Inflation

Interest rates, set by central banks, affect the cost of borrowing money. Lower rates can
encourage investment and spending, while higher rates can slow them down. Inflation is the
rate at which prices for goods and services rise, eroding purchasing power. Entrepreneurs
must consider these factors when planning investments and pricing.

Economic Indicators

These are statistics that provide insights into the health of the economy. Key indicators
include GDP growth, unemployment rates, and consumer confidence. They can signal
changes in the business cycle and help entrepreneurs make informed decisions.

Business, Innovation and AI

In the next section we will do a deep-dive into the potential use of AI for businesses - the
ways AI can be and are currently used in different business roles.

First, let's do a knowledge check.

Key Points

1. 1

AI is being integrated into businesses of all sizes and sectors, enhancing roles and efficiency,
and fostering innovation within economic and governmental frameworks.

2. 2

Entrepreneurs use AI to create new products or services, taking risks to establish businesses
that can lead to profit, growth, and sometimes fame, while social entrepreneurs focus on
societal impact.

3. 3

Essential skills for success in business include financial acumen, analytical skills, leadership,
strategic thinking, and understanding market needs, all of which can be improved through
learning activities and will be essential to using AI tools within a business function.

Click the Continue button to continue to Lesson 3: AI and Business and Entrepreneurship.

Welcome to Lesson 3 of the Business and Entrepreneurship deep dive.

In this lesson you will explore the crucial role of Artificial Intelligence (AI) in shaping modern
enterprises. You'll uncover how AI's ability to mimic human thought processes is
revolutionizing the way companies operate by streamlining data analysis, task automation,
and strategic decision-making. Through interactive activities, you'll connect real-world
business scenarios with AI solutions, reflecting on your own understanding of AI's business
impact. You'll also read case studies and discover how AI is redefining job roles across
industries. By the end of this lesson, you'll have a clearer vision of how AI skills can enhance
your career prospects and drive innovation in the business sector. Let's get started!

Introduction to AI in Business

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are
programmed to think and learn like humans. In the business world, AI's significance lies in its
ability to analyze large volumes of data quickly, automate repetitive tasks, enhance decision-
making, and foster innovation. By leveraging AI, businesses can gain a competitive edge
through improved efficiency, personalized customer experiences, and the development of
new products and services. AI is transforming industries by enabling smarter operations and
providing insights that were previously inaccessible.

See below how the different business functions listed in the previous section can use AI:

AI can analyze customer data to predict buying patterns, recommend products, and
personalize sales strategies. It can also automate routine tasks like lead qualification and
follow-ups.

AI tools can tailor marketing campaigns by analyzing consumer behavior, optimizing ad

placements, and creating personalized content. Chatbots can engage with customers in real-
time, providing support and gathering insights.

AI can automate transaction processing, detect fraud through pattern recognition, and
provide predictive analytics for financial forecasting and risk management.

AI can streamline the recruitment process by sorting through resumes, predicting candidate
success, and automating routine HR tasks. It can also assist in employee engagement and
performance analysis.

AI can optimize supply chain management through predictive analytics, enhance inventory
control with demand forecasting, and improve production planning with machine learning
algorithms.
AI can help manage and monitor IT infrastructure, predict hardware failures, optimize data
storage, and enhance cybersecurity through anomaly detection and automated threat
responses.

AI-powered chatbots and virtual assistants can handle customer inquiries, provide instant
support, and free up human agents for more complex issues. AI can also analyze customer
feedback to improve service.

AI can analyze spending patterns, predict market trends, and automate the procurement
process. It can also assist in supplier selection and risk management by evaluating supplier
performance data.

AI can assist in document analysis, contract review, and legal research by quickly processing
large volumes of text and identifying relevant information, reducing the time spent on
manual review.

Entrepreneurship Case Study: Vivienne Ming

Dr. Vivienne Ming

Dr. Vivienne Ming is a notable entrepreneur, theoretical neuroscientist, and artificial
intelligence expert; her work is at the intersection of education, technology, and social
reform.

Ming's entrepreneurial endeavors are deeply rooted in her personal experiences and her
drive to create positive societal impact. As a transgender woman, she has been an avid
advocate for LGBTQ rights and diversity in the tech industry.

Ming has many notable projects and startups as a result of her ongoing entrepreneurship
and innovation. She co-founded Socos Labs, an independent think tank, where she has been
instrumental in developing AI-based tools designed to augment human capabilities,
particularly in the context of education and workforce development. Another prominent
achievement was her creation of Muse, an AI-based app that predicts the future life
outcomes of children and offers personalized recommendations to help improve those
outcomes.

Ming doesn't just focus on commercial success; she is dedicated to ethical AI development
and frequently speaks on the importance of responsible innovation that benefits all
segments of society.

AI in Small Business

Small businesses often are operating with limited resources or budget to complete all of
their activities or extend beyond their current practices to grow the business. AI can provide
small businesses with cost-effective solutions to optimize their operations, enhance
customer experiences, and make data-driven decisions that can lead to growth. Here are a
few short examples of how AI can assist small businesses:
Case Study: AI for Employee Engagement, Development and Performance Evaluations

AI is revolutionizing employee engagement by offering personalized insights into individual

values, motivations, and goals, while providing real-time feedback to enhance team
communication and streamline onboarding processes. Tools like Genpact's Amber
chatbot proactively monitor employee satisfaction, enabling quick performance
adjustments and job satisfaction. AI's capability to analyze performance data allows
for tailored rewards and recognition, fostering a culture of motivation and
retention. Additionally, AI's monitoring of work patterns and stress indicators informs
managers on how to support work-life balance and prevent burnout.

By automating mundane tasks, AI empowers employees to engage in more meaningful

work, aligning with the company's vision and increasing overall job satisfaction. AI also acts
as a sophisticated career coach, guiding personal development and career progression. The
implementation of AI tools can be tracked to measure their impact across departments, with
employee feedback guiding continuous improvement and strategic decision-making.

Video

Watch the short video below, "How AI Could Empower Any Business" by Andrew Ng
(YouTube, 11:16 minutes) to learn more about AI use cases for business.
© 2024 TED To learn more about TED, visit TED.com

How AI Could Empower Any Business | Andrew Ng | TED

AI Skills in Business and Professional Services

Let's take a look at some of the benefits of AI skills for efficiency and innovation:

Click on the plus signs to learn more.

UpStart

Since it started in 2020, Upstart, a company that uses artificial intelligence, has become
quite popular. Upstart wants to change the old way of checking if someone can borrow
money by using an AI-based model instead. Upstart looks at a lot of information—1,600
different things about a person and 15 billion bits of data—to figure out if someone is likely
to pay back a loan. Upstart's goal is to use its smart technology to make it easier for more
people to get loans. It also believes that its computer program is better at guessing who will
pay back their loans than the usual methods.

JPMorgan Chase

Big banks like JPMorgan Chase aren't being left behind in using artificial intelligence; they're
right in the mix. JPMorgan Chase uses AI for things like spotting fraud and improving how
they help customers. They've even used an AI similar to ChatGPT to study what the Federal
Reserve has been saying for the past 25 years, hoping to find clues that will help them make
better trading decisions. AI is also big in the world of automated trading, which is why it's no
surprise that JPMorgan Chase is using it to boost their trading activities. Big banks do a lot of
research, and AI has been a huge help for JPMorgan, saving them hours every day. It quickly
pulls up needed information and assists in making choices.

EY leverages AI to transform tax services by implementing an AI-powered platform that

automates tax research and data analysis. The platform uses natural language processing to
interpret complex tax laws and machine learning to provide predictive insights, resulting in
increased efficiency, improved accuracy, and personalized client service. This integration of
AI allows tax professionals to focus on strategic advisory roles, enhancing overall client
satisfaction and maintaining the EY organization's competitive edge in the professional
services sector.

Optional Learning

If you're interested to learn more about the role of AI in business, listen to this podcast by EY
Better Heroes (Duration 26:08 minutes).

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%2Fepisode%2F6d2YrOJyqINSkNOPTHekJK%3Futm_source
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%2Fab67656300005f1fc18d7d30cc493f39d79076fe&key=40cb30655a7f4a46adaaf18efb05d
b21&type=text%2Fhtml&schema=spotify

What AI Skills are in demand in Business?

In the rapidly evolving job market, some AI skills stand out as particularly in-demand and
lucrative:
Learning Activity

Click the link below to Codecademy's course, 'Write a Sales Outreach Email with Generative
AI Case Study'. This course takes less than an hour and will give you the chance to practice
using AI for business, writing a sales outreach email for business-to-business marketing.

Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.

Write a Sales Outreach Email with Generative AI Case Study | Codecademy

Driving AI Development in Business and Government

Humans have the power to shape how AI will influence the future of business. To learn
more, read this article(opens in a new tab) that explains how new technologies can be
designed to complement workers’ skills or have built-in upskilling to support sustainability of
jobs.
Governments around the world are increasingly recognizing the transformative potential of
AI for businesses and the wider economy. By harnessing the power of AI, countries can drive
innovation, increase productivity, and maintain competitive advantages on the global stage.
To facilitate the growth and integration of AI technologies, governments are taking various
initiatives.

The National AI Centre (NAIC) was established in 2021 to support and accelerate Australia's
AI industry. It aims to help Australia become a global leader in developing and adopting
trustworthy, secure, and responsible artificial intelligence.

NAIC is doing this by:

 supporting AI adoption for small and medium businesses by addressing barriers and
challenges

 growing an Australian AI industry

 convening the AI ecosystem

 uplifting safe and responsible AI practice

The United Kingdom has also been proactive in fostering an environment conducive to AI
development. The UK government has established an AI Sector Deal, which is a major
investment aimed at boosting the UK's position as a leader in AI technology. This deal
includes funding for AI research, development of AI skills, and partnerships with industry to
create jobs and drive economic growth.
The country is already harnessing AI technology to address critical needs in agriculture,
healthcare, education, and financial services, through a combination of strategic
government-led initiatives, a thriving tech, start-up and private sector ecosystem, innovative
partnerships, as well as a vibrant civil society.

In Kerala, India, the state government integrates AI into education and public services, with
institutions like IIITM-K and NIT Calicut leading in AI research and education. Kerala's
industrial policy prioritizes AI. Thiruvananthapuram is the focal point for AI innovation, and
incubators support entrepreneurs in transforming ideas into practical AI solutions across
various sectors, positioning Kerala as a significant player in India's AI landscape.

Brazil, the largest economy in Latin America, wants to achieve technological autonomy and
competitiveness in the AI sector, aiming for what it called "national sovereignty" instead of a
reliance on imported AI tools from other countries. The proposed investment plan foresees
resources for "immediate impact initiatives" in sectors such as public health, agriculture,
environment, business and education. The 23.03 billion reais proposed for the AI investment
plan will be disbursed from 2024 to 2028, according to the Brazilian government.
Key Points

1. 1

AI is transforming business operations by automating tasks, enhancing decision-making, and

driving innovation, with an emphasis on efficiency, personalization, and competitive
advantage.

2. 2

Prompt engineering, data analysis, and continuous learning are in-demand AI skills that can
boost employability and adaptability in the evolving job market.

3. 3

Governments worldwide are investing in AI to foster innovation and economic growth, with
initiatives like Australia's National AI Centre, the UK's AI Sector Deal, and Kenya's strategic
tech integration.

Congratulations!

You have reached the end of the Business and Entrepreneurship module. Next, you will
explore the Technology module and learn about the impact of AI on technology and careers
associated with it.
Welcome to the Industry Deep Dive - Exploring AI Skills in Technology.

This deep dive will introduce learners to technology-focused careers, with an introduction to
areas of Information and Communication Technology (ICT), software engineering, data,
coding & analytics – and how AI is used and created in these roles.

This deep dive will conclude with guidance and resources for further education, job-
searching, and finding employment within the Technology sector, with relevance for using or
creating AI.

Welcome to the Technology Deep Dive

2. Introduction to Technology, Software, and Coding

3. AI and Technology

4. Introduction to Tech Careers

Video

Watch the video below, featuring an AI-generated teacher, to welcome you to the
Technology deep dive.
Welcome to Lesson 2 of the Technology deep dive.

In this lesson you will learn about the technology sector and one of the most fundamental
components: software and programming. You'll learn how to distinguish between hardware
and software, while understanding how these components interact with each other to
create the whole 'computer' or 'machine'. We will introduce you to programming languages,
explaining concepts like syntax, semantics, and different programming paradigms. You'll also
explore the transformative potential of AI in coding, and the many ways it can assist in the
programming development process. Practical activities include Codecademy courses on
foundational programming skills and using AI for coding, providing hands-on experience.

What is the Technology Sector?

The Technology (or Tech) sector is a category of businesses, organizations, and institutions
that develop, manufacture, and market various technologically based goods and services.
Examples of goods in this sector could include electronics, computers, smart devices,
robotics and software applications; services can include, for example, software
development, cybersecurity services, and data analytics.

Information Technology (IT) is a subset of the Tech sector that specifically focuses on the
development, implementation, and maintenance of computer systems and software, with
services that support the processing and management of data.

In this lesson, our focus will be on the IT sector, which is fundamentally involved with
computer systems, software, and data processing, and thus plays a pivotal role in the
development of Artificial Intelligence.

Video

Watch the short video below, "Information Technology in 4 Minutes" (YouTube, 4:30
minutes) to learn more about the IT sector.

Information Technology In 4 Minutes

Hardware vs Software

Every technology is essentially the combination of two things: hardware and software. These
fundamental components work together to perform the tasks associated with that
technology.
Hardware refers to the physical components of a technology; it's everything that you can
touch and see. In computers, this often includes:

The main circuit board that connects all components of the computer, allowing them to
communicate with each other.

Known commonly as a "processor", the CPU is the 'brain' of the computer, which performs
calculations and runs programs.

Temporary storage that allows the CPU to read and write data currently in use by the
computer.

A specialized processing unit that handles graphics and image rendering.

A device used to store and retrieve digital data.

Another device used to store and retrieve data using flash memory, which is much faster
than HDD.
Specific type of memory used by the GPU.

Additional devices which can be connected, such as webcams or game controllers.

Software, unlike hardware, cannot be seen or touched. It is the set of instructions that tell
the computer what to do. In computers, the code we see running on the hardware includes:

The main software which manages all the hardware and other software on the computer.
Popular operating systems include Windows (Microsoft) or macOS (Apple).

A software application that provides the facilities needed for programmers to consolidate
the different aspects of writing a computer program.

A special program that translates certain types of code (known as high-level code) so the
computer can understand it.

Video

Watch the short video below, "Computer Basics: Inside a Computer" (YouTube, 2:16
minutes) to learn more about the main hardware components of a computer.
Computer Basics: Inside a Computer

Programming Languages

To build systems and software, programming languages (or coding languages) are used
to essentially tell the computer what tasks to execute, and how. Programming languages
are used by professionals, such as software engineers and data scientists, to write code.
Code is essentially a set of instructions for the computer.

There are a variety of different programming languages which are used for a variety of
different reasons. Each programming language has its rules and structure (similar to human
languages) which define how the code needs to be written and understood by the
computer / machine. Let's take a look at some of the key aspects of a programming
language:
Practice Activity

Click the link below to Codecademy's course, 'Learn How to Code'. In this course, you will
learn the foundational skills needed to help you understand any programming language you
wish to learn. This course will take approximately 2 hours to complete - but go at your own
pace!

Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.
Learn How to Code | Codecademy

Different Coding Languages

There are many different coding languages out there, all of which are used in different
applications and contexts, depending on the requirements of the program. Some popular
and widely used programming languages are listed below:
Practice Activity

Want to learn a programming language? Let's do it!

Click the link below to Codecademy's course, 'Build Connect Four Using Python'. In this
course, you will be walked through all the steps necessary to build your own connect-four
game using Python! This course should take less than an hour to complete, but go at your
own pace!

Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.

Build Connect Four Using Python | Codecademy

AI for Coding
As established, coding takes form in a programming language. Much like when learning
human languages, we need to learn the rules, structure and components of a programming
language in order to successfully use it.

We've already established that AI can learn human languages, so what about programming
languages? Yes, it can do that too!

AI has shown great transformative potential to streamline the software development

process for programmers by reducing the manual efforts required to write code. By using AI
in the coding and software development process, programmers can focus on more complex
or creative tasks.

Using generative AI, programmers can prompt it to describe what the coding language is and
what they want it to do; then, the AI can produce code snippets or even full functions -
speeding up the entire development process. Not only can AI write code, but it is also an
incredibly useful tool for programmers to detect bugs, vulnerabilities or issues in their code.
It can even find ways to make the code more readable or perform better.

Practice activity

Click the link below to Codecademy's course, 'Learn How to Use AI for Coding'. In this
course, you'll get to understand the ways in which GenAI are being used for coding, as well
as the basics of prompt engineering for coding and software development.

Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.

Learn How to Use AI for Coding | Codecademy

Key Points

1. 1

The technology sector is a vast field. This lesson specifically focuses on information
technology; the development, implementation and maintenance of computer systems and
software, with services that support the processing and management of data.

2. 2

The lesson clarifies the distinction between hardware (physical components of technology)
and software (instructions that tell the computer what to do), and how they interact with
each other.

3. 3

It introduces programming languages, explaining key concepts like syntax, semantics, and
different programming paradigms such as procedural, object-oriented, and functional
programming.

4. 4

There is transformative potential of AI in coding, including its ability to generate code, assist
in debugging, and streamline the software development process, allowing programmers to
focus on more complex tasks.

Welcome to Lesson 3 of the Technology deep dive.

In this lesson you'll learn how advancements in computing power, big data, cloud
computing, and specialized hardware are propelling AI forward, while AI, in turn, is
revolutionizing technology careers and industries. The lesson features case studies of AI
pioneers like Demis Hassabis and Fei-Fei Li, highlighting their contributions to AI's evolution.
You'll explore AI's transformative impact on various tech roles, including software
engineering, data science, gaming, and cybersecurity, through interactive flashcards. The
lesson also addresses the future potential of AI, from enhancing human capabilities to
ethical considerations, and prepares you for the changing landscape of tech careers driven
by AI advancements.

Tech Transforms AI

Watch the video below, featuring an AI-generated teacher, to learn about the linkages
between Tech and AI.
Case Studies of AI Pioneers

Explore on the following slides, case studies of impactful people who have contributed to
the use and creation of AI.

START
Case Study 1

Demis Hassabis, Co-Founder and CEO of DeepMind

British Computer Scientist Demis Hassabis is a pioneering figure in the field of artificial
intelligence, known for co-founding DeepMind Technologies. Hassabis' work has been
instrumental in advancing the capabilities of AI through projects like AlphaGo, the first
computer program to defeat a world champion in the complex board game Go. His work
focuses on creating AI that can learn and master a variety of tasks, pushing the boundaries
of machine learning and contributing to scientific discoveries.

Case Study 2

Fei-Fei Li, Co-Director of the Stanford Human-Centered AI Institute

Fei-Fei Li, a Chinese-American Computer Scientist, is a prominent computer scientist and

advocate for diversity in technology and AI. She is renowned for her work in computer vision
and cognitive neuroscience, particularly for creating ImageNet, a large visual database
instrumental for advancements in deep learning. At Stanford, she works on AI's
humanitarian impact, aiming to ensure that AI technology benefits all of humanity. Li also
co-founded AI4ALL, a nonprofit dedicated to increasing diversity and inclusion in AI
education, research, development, and policy.
Case Study 3

Yoshua Bengio, Co-Founder of Element AI

Yoshua Bengio(opens in a new tab) is a Canadian computer scientist recognized for his
extensive work in artificial intelligence and deep learning. As a co-founder of Element AI and
a professor at the University of Montreal, Bengio has been a driving force behind the
development of neural networks and machine learning algorithms. His research has
significantly advanced the understanding of how AI can process language and images,
leading to practical applications that impact various industries. An example for this is when
you upload an image to social media, it will suggest to tag those in the image, based on
image recognition from your friends' profiles. Alongside his contemporaries, Bengio was
awarded the Turing Award for his contributions to the conceptual and engineering
breakthroughs that have made deep neural networks a critical component of computing.

Case Study 4

YOU!

You can make a great contribution to AI! Just one way in which youth can make a start in
contributing to AI is through making developments in the ethical and responsible use of AI.
EY-Microsoft is actually hosting the "2024 EY-Microsoft Open Science Data Challenge:
Coastal Resilience"

The EY-Microsoft Open Science Data Challenge gives university students and early-career
professionals the opportunity to use data, artificial intelligence and technology to help build
a sustainable future for society and the planet.

If you're interested, you can apply here(opens in a new tab).

Many different tech fields are being influenced by advances in AI. Let's take a look below at
some examples of the ways AI is transforming different fields of Technology:

AI can be used to aid in the development of code; AI can speed up the process of coding and
programming by writing code for the user with a few simple prompts. AI can also be used to
review code and software design, finding ways to make it more efficient, or remove bugs and
vulnerabilities.

AI can be used to automate machine learning, allowing data scientists to more efficiently
build models. AI can also help data scientists to enhance predictive analytics by building
more accurate and complex models. Finally, AI can be used to scan data to determine any
anomalies or outliers, making it particularly suited to data cleaning and fraud detection.
AI is having a profound influence on the gaming industry. AI can be used to create more
realistic and complex behaviors for Non-Playable Characters (NPCs); AI can also be used to
tailor the gaming experience, to make the game more challenging or engaging, by learning
the player's skills and preferences. To speed up the game development process, AI can be
used to test games and identify bugs or glitches.

AI is significantly enhancing the capabilities of security systems to detect, prevent and

respond to cyber threats. For example, AI can be used to analyze mass amounts of network
traffic and identify any unusual patterns that may indicate a cyber threat. In containing a
potential breach, AI can also be used to automate the response to threats by isolating
affected systems; blocking IP addresses; and, terminating harmful processes.

AI is transforming technology and hardware by embedding intelligent algorithms into

devices, leading to more efficient and adaptive machines, such as smart IoT devices and
advanced robotics, which improve performance and drive innovation. As of recently,
computer hardware has been evolving in-line with AI progress; for example, some
computers now contain Neural Processing Units (NPUs) which are specifically designed to
process machine learning tasks.

The Potential of AI in Future Tech

As we look ahead, the potential of AI in shaping future technology is immense and

multifaceted. AI is set to be the driving force behind transformative changes across all tech
industries.

AI promises to revolutionize the way we interact with devices, access information, and
solve complex problems. The predictive capabilities of AI are expected to become more
accurate, leading to advancements in fields like personalized medicine, autonomous
transportation, and smart energy management.
The ethical and responsible development of AI will remain a crucial consideration, ensuring
that the benefits of AI technologies are distributed equitably across society. As AI continues
to evolve, it will open up new career paths and educational opportunities, requiring a
workforce skilled in AI literacy and ethics.

Case Studies: AI and the Tech Industry

Below, let's take a look at some cases of innovative AI entrepreneurship specific to the Tech
industry.

START

Case Study 1

Ivan Zhao

Notion, led by cofounder Ivan Zhao, is a productivity startup valued at USD$10 billion.
Initially struggling, the company pivoted to a minimalist productivity tool, blending features
of Google Docs, wikis, and to-do lists. After a successful launch on Product Hunt in 2016,
Notion became profitable and gained popularity for its customizable interface. It now
approaches 100 million users and made $250 million in revenue last year. Notion's AI bot,
part of its aggressive AI strategy, earned it a spot on Forbes' AI 50 list.

Case Study 2

Aravind Srinivas, Denis Yarats, Johnny Ho and Andy Konwinski

Perplexity is an AI-powered search engine that provides concise, conversational search

results with citations, challenging traditional search technology. Founded by Aravind
Srinivas, Denis Yarats, Johnny Ho and Andy Konwinski, the startup is valued at USD$1 billion.
It boasts 15 million users with features like personalized AI profiles and database-specific
searches. Perplexity's rapid growth and innovative approach have attracted significant
attention from major tech companies and investors, with the company's success hinged on
providing quick, accurate information without directly competing with Google, offering an
alternative for users seeking summarized content.
Case Study 3

Hans Jørgen Wiberg

Hans Jørgen Wiberg created "Be My Eyes", the company that connects people who are blind
or have low vision with sighted volunteers and companies through live video and AI. When
someone with a visual impairment needs assistance with a task that requires sight, they can
use the app to request help. A sighted volunteer receives a notification and can then answer
the call to help with whatever the person needs. This app has been enhanced with the use
of AI; watch this video(opens in a new tab) to find out more!
Key Points

1. 1

Advancements in computing power, big data, cloud computing, and specialized hardware are
essential for the development of AI, which in turn is revolutionizing various tech careers and
industries.

2. 2

The lesson features case studies of AI pioneers like Demis Hassabis and Fei-Fei Li, showcasing
their contributions to AI's evolution and the transformative impact they have had on
technology and society.

3. 3

AI is creating new demands for tech professionals with skills in programming, data analytics,
and understanding of neural networks. It's also fostering cross-disciplinary collaboration and
introducing new roles such as AI Product Manager, indicating a shift in the tech industry
towards AI-centric careers.

Click the Continue button to continue to Lesson 4: Introduction to Tech Careers

Welcome to the final lesson of the Technology deep dive.

In this lesson you will explore the various job roles within IT, including software
development, cybersecurity, data science, and more. The deep dive emphasizes the diversity
of careers available, each requiring specialized skills and knowledge. You'll also discover the
significance of IT in driving innovation and its influence across different sectors. Interactive
elements like flashcards will provide examples of specific IT roles, and a learning activity
from Codecademy will offer insights into choosing a career in tech.

What are Tech Careers?

The Tech sector is huge - and it's only growing. In Information Technology (IT), there are a
wide range of job roles and professions. It encompasses a diverse range of professions
dedicated to the design, development, implementation, support and maintenance of
computer systems, software applications, and networks. The tech industry is synonymous
with groundbreaking innovation, a fast-moving environment, and a profound influence that
extends across different fields and the overall economy.

There is such a wide variety of roles in the IT sector, each with its own niches, specializations
and skillsets.

What kind of work can I do with an IT job?

We've established that the IT sector is vast, encompassing a range of fields and professions.
Tech careers often require professionals to specialize in a particular area, given the
complexity of the field. See below a snapshot of some of the examples of work you could do
in Information Technology:
 Front-End Developer: specializes in the user interface and user experience aspects of
software, working with programming languages like HTML, CSS, and JavaScript.

 Back-End Developer: focuses on server-side logic, databases, and application

integration.

 Full-Stack Developer: handles both front-end and back-end development tasks.

 Mobile App Developer: develops applications for mobile devices, using platforms like
iOS and Android.

 Systems Analyst: designs information systems solutions to help organizations operate

more efficiently.

 Business Analyst: works with businesses to integrate technology solutions that meet
their needs.

 IT Project Manager: oversees technology projects from start to finish, ensuring they
meet business requirements.

 Information Security Analyst: protects computer networks and systems from cyber
threats.

 Penetration Tester (AKA Ethical Hacker): simulates cyber-attacks to identify and fix
security vulnerabilities.

 Security Architect: designs, builds, and oversees the implementation of network and
computer security for an organization.

 AI Security Researcher: leverages AI to help solve cybersecurity issues or challenges.

 Data Scientist: uses statistical analysis and machine learning to interpret complex
data and extract insights. Data science can be used in nearly any context or industry,
and deals with a broader range of data analytics tasks, including data cleaning,
exploration, visualization, and statistical analysis.

 Data Analyst: collects, processes, and performs statistical analyses on large datasets.

 Business Intelligence (BI) Developer: creates data-driven reports and dashboards for
business decision-making.

 AI Data Scientist: a more specialized data scientist who focuses on AI and machine
learning.

 Network Administrator: installs, supports, and manages computer networks and

systems.

 Systems Administrator: ensures that the computer systems and servers are running
efficiently and securely.

 Database Administrator (DBA): specializes in managing and maintaining database

management systems.

 AI Network Analyst: combines expertise in networks and systems with knowledge of

artificial intelligence to manage, analyze, and optimize systems administration.

 Cloud Engineer: designs and manages cloud infrastructure and platform services.

 Cloud Architect: develops cloud computing strategies for storage.

 Cloud Consultant: advises organizations on cloud adoption and migration strategies.

 AI Cloud Engineer: specializes in designing and implementing cloud-based AI
solutions, ensuring scalable and efficient deployment of AI applications within a
cloud computing environment.

*Note, cloud computing is like having a super powerful computer that you can access from
anywhere through the internet. Instead of saving all your photos, documents, or even
running programs on your own computer, you save them on servers in the 'cloud'. These
servers are just computers that are kept in big buildings called data centers, and they're
connected to the internet all the time.

 AI Research Scientist: conducts research to advance the field of artificial intelligence.

 AI Engineer or Developer: designs and develops a variety of AI algorithms and

models, using a range of different machine learning methods.

 AI Application Developer: implements AI technologies in practical applications and

products.

 AI Project Manager: oversees the planning, execution, and delivery of AI projects,

ensuring that tasks are completed efficiently with enough resources, meeting the
goals and timelines of the project.

 UX Designer: focuses on the overall feel of the product and user satisfaction.

 UI Designer: concentrates on the look and layout of the product interface.

 Interaction Designer: designs engaging interfaces with well thought-out behaviors.

Video

Watch the optional video below, "Essential Training and Tips to Accelerate your Career in
AI" by NVIDIA (1 hour) to learn more about the ways in which you could build a career in AI

Essential Training and Tips to Accelerate Your Career in AI | Other 2024 | NVIDIA On-
Demand

Learning Activity
Click the link below to Codecademy's course, 'Choosing a Career in Tech'. This course takes
less than an hour, and gives you the chance to learn more about different Tech careers and
considerations when choosing a career in tech.

Please note: you will need to sign up and log into your free Codecademy account to complete
this practice activity.

Choosing a Career in Tech | Codecademy

Key Points

1. 1

There are many specialized job roles within the IT sector, including software development,
cybersecurity, and data science.

2. 2

There are many opportunities to work with AI in a tech role, both as an added skill and as a
specialist career area.

3. 3

The IT sector is crucial for driving innovation and has a significant influence on various other
sectors and the economy.

4. 4

Due to the complexity of technology, IT careers often require professionals to develop

specialized skills in specific areas.

Congratulations!

You have reached the end of the Technology deep dive. Next, you will explore the
Employability module to finish the EY-Microsoft AI skills passport course and receive your
certificate of completion!
Welcome to the final module in the EY-Microsoft AI Skills Passport. After completing your
learning in AI and industry deep dives into Sustainability, Technology, and Business and
Entrepreneurship, we conclude the course with the Employability module, where we'll
give you some important tools you'll need for success in today's job market and in future job
markets.

This module is divided into two comprehensive lessons:

 "Preparing for a Career," offers guidance on self-assessment, skill development, and

strategic planning to align your interests and aspirations with the realities of the
workforce.

 "Landing a Job," transitions into the practicalities of job hunting, covering topics such
as crafting an effective resume, mastering the art of the interview, and effective
networking strategies.

Together, these lessons aim to not only prepare you for the job market, but also to enhance
your chances of securing a position that aligns with your career goals. Throughout this
module, you will be given guidance and resources for using AI as a tool to enhance your
career planning and job searching.

Welcome to the Employability Module

2. Preparing for a Career

This lesson is currently unavailable

Lessons must be completed in order

3. Landing a Job
Video

Watch the video below, featuring an AI-generated teacher, to welcome you to the
Employability module.

Click the Continue button to continue to Lesson 2: Preparing for a Career

Welcome to Lesson 2 of the Employability module.

In this lesson you will learn strategies for launching and advancing a career with AI. The
lesson covers the distinction between jobs and careers, emphasizing the importance of
reflection, research, and planning in building a long-term career. You'll explore the basic
requirements for a career, including education, skills, experience, and professional
networking. Additionally, the lesson provides guidance on setting SMART goals, obtaining
relevant education and certifications, and gaining experience through internships,
bootcamps, and volunteering. By the end of this lesson, you'll have a clearer understanding
of how to strategically approach career planning and development.

Employment in your area of interest

Finding a job can be both a challenging yet exciting journey - and it can be hard to know
where to start! Whether you're looking for your first job or your next job, a strategic and
thoughtful approach to job searching is essential.

There are many reasons why someone goes searching for a job. For example: to earn money;
to gain new skills and experience; to excel at something and get good at it; to contribute to
their community and wider society; to seek personal fulfilment; and to challenge oneself.
Job vs Career

There are some fundamental differences between landing a dream career, as opposed to a
dream job. So how different are they?

While both jobs and careers enable us to earn money, these are not the same thing.

For the remainder of this module, we will be focusing on ways in which to build a career in
your area of interest. While we have chosen to focus the AI Skills Passport on
the Sustainability, Technology, or Business sectors, this employability module can be
applied to any industry you may be interested in.

Video

Watch the video below, "Future of Work Initiative - EY: Exploring Careers, Iulia Popescu". In
this video, Iulia explains her journey into an AI-focused career, and what made her
interested in AI after completing her studies in a different field.

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d_1280&key=40cb30655a7f4a46adaaf18efb05db21&type=text%2Fhtml&schema=vimeo
- Building a Career

Let's first take a look at some of the basic requirements for a career in any field - be it
Sustainability, Business and Entrepreneurship, or Technology:

Education

Many careers require tertiary education and professional qualifications in order to work in
this sector. Some examples of careers that may require professional qualifications include:

Sustainability Business Technology

- Environmental or Climate - Market Research Analyst - Software Engineer

Scientist
- Marketing Associate - Network Architect
- Energy Analyst
- Project Manager - AI Developer
- Human Rights Lawyer
- Finance Manager - Cyber Security Analyst
- Green Building Architect

Thankfully, not all jobs or careers require qualifications! There is a diverse range of options if
you don't want a university degree; you could do a trade, get an apprenticeship, or simply
gain the skills and knowledge you need through your work. For example, jobs that often
don't require a degree include:

Sustainability Business Technology

- Farmer or Agricultural Worker - Entrepreneur - Web Developer

- Salesperson/Sales Representative
- Park Ranger or Forest Worker - App Creator
- Administrative Assistant
- Firefighting and other natural - Event Planner - IT Support Specialist
disaster responses
- Network Administrator
- Eco Landscaper

- Waste Management Jobs

The options for education are vast, and you have many options available to you based on the
career path you choose.

- Skills

Each field and area of employment within your sector of choice will have a typical set of
skills required for workers to perform the tasks associated with their role. These skills
requirements will be largely similar for the same role, although may differ between
employers depending on the needs of their business or organization.
Although skills have been discussed throughout the general and topical streams, as a
reminder, these can include technical skills like science skills or quantitative skills, and soft
skills such as time management and effective communication. In addition to these technical
and soft skills, AI skills are extremely in-demand across the topical learning areas; these will
be discussed later.

- Experience

Most roles will require you to have skills and knowledge gained through previous
experiences (both paid and unpaid). While this usually isn't the case for entry-level (early
career) jobs, this is essential as one progresses to more senior roles in their career.

Some employers and organizations may also desire the following:

- Professional membership or association

An organization that professionals can join to get access to resources, support and
networking opportunities. This can provide a range of benefits, keeping professionals up to
date on industry news and professional development programs, while also setting the
standards for the profession as a whole.

- Accreditation

Professional accreditation is a recognition provided to individuals who have met certain

standards in their field. This often requires further education (usually external to typical
institutions such as University) and serves as formal endorsement of an individual's skills and
capabilities.

- Networks

Networks are professional connections with others in the field. These can be formal or
informal and provide opportunities for individuals to connect with others, share knowledge,
learn about job openings and collaborate. Networks, while not a necessary component for
landing a job or career, are extremely beneficial as it gives you a 'person on the inside' who
can guide you on areas for upskilling and advocate for you in the job application process (if
it's at the same organization).

Where do I start?

Watch the video below, featuring an AI-generated teacher, to learn about the various
strategies you can use to find a career path that excites you.
Education and Skills
In the very early stages of your career, two of the most vital things we usually need are
education and skills. Thankfully, there are many options out there for obtaining these.

Education for some professions in the early stages is usually gained through tertiary
institutions such as university and college, and many professions will usually require at least
a Bachelor's level degree or higher in a field relevant to the role. There's plenty of
information online about university degrees and institutions near you, which you can
research to inform your choice of institution.

However, as established earlier, a formal education is not always necessary, and there any
many options out there that will allow you to achieve your aspirations through a range of
different pathways. Some other options to gain relevant knowledge that could help you
enter into a job or career of choice could include:
When it comes to skills, the typical method of gaining these are through on-the-job training
after landing a role. But did you know there's a ton of other ways to upskill or reskill? For
example:
Global Certifications

Want to stand out with a professional certification? Check out our list of globally-recognized
certifications for sustainability, business and entrepreneurship, and technology! These are
short courses or exams that advocate your skills. While many are created for more seasoned
professionals, you'll find many offer certifications for students and budding professionals
too.
AI and Careers

As we have established, AI is transforming industries and business across the globe.

Organizations are increasingly looking for candidates with AI skills, as having AI-skilled
employees allows them to stay competitive through innovation, harness data-driven insights
for strategic decision-making, and automate tasks to focus on higher-value work.

To further illustrate, consider the following statistics:

1. 64% of businesses expect AI to increase productivity. This is extremely attractive to

businesses and incentivizes them to adopt AI in some capacity.
- Haan, K. (2024). 22 Top AI Statistics And Trends In 2024. Forbes
Advisor. https://www.forbes.com/advisor/business/ai-statistics/(opens in a new tab)

2. 2
AI is expected to see an annual growth rate of 37.3% from 2023 - 2030. Simply put, an
annual growth rate of this level is substantial and is already impacting multiple facets of our
personal and professional lives. This means we can expect AI to become more prominent
over the coming years.
- Maheshwari, R. (2024). Top AI Statistics And Trends. Forbes Advisor
India. https://www.forbes.com/advisor/in/business/ai-statistics/(opens in a new tab).
Key Points

1. 1

There is a difference between a job and a career. Careers are long-term goals and objectives
that require sustained effort and planning.

2. 2

There are a series of steps involved in preparing for a career, including personal reflection,
research and planning.

3. 3

There is a lot of value in formal education, certifications, and practical experiences like
internships to gain the necessary skills and knowledge for career advancement. There are
various opportunities to learn and gain skills beyond formal tertiary education, with many
jobs available for people who don't bring a university degree.

4. 4

There is a focus on continuous learning, and it is encouraged that new job seekers look for
professional development opportunities to achieve sustained personal growth, advantages
in job seeking, and fulfilment.

Click the Continue button to continue to Lesson 3: Landing a Job

Welcome to the final lesson of the Employability module and the EY-Microsoft AI Skills
Passport.

In this lesson you will learn about the various processes involved in the job application
process, and what you can do to land a job in your sector of choice. This lesson will cover the
fundamental documents needed to apply for job, various job-searching methods, how to
network, and the various considerations for a successful interview. This lesson concludes
with examples of job advertisements across Sustainability, Business, and Technology. Let's
get started!

Starting your Job Search

Let's get ready to find a job! This can be a challenging process, but extremely rewarding -
especially if you're able to land the job you really want.

There is no one pathway to landing a job, and this can really differ depending on the
individual, their aspirations and career interests, the organizations they're applying for, and
more. Overall, there are some key activities and processes involved, which we discuss in the
remainder of this lesson. This includes:
Using AI to Assist in the Job Searching Process

Would it surprise you to learn that you can even harness the power of AI to help you
throughout the job searching process? You sure can!

AI can be beneficial throughout your journey from job application to (hopefully) a job
acceptance. For instance, you can:

Throughout the remainder of the course, we provide many links to specific AI tools you
can utilize in the application process.

While we recommend utilizing AI in the job application processes, it is worth noting that
using AI to replace your own efforts entirely is not a responsible, fair, or ethical use of AI.
For example, you shouldn't copy and paste information directly from an AI chatbot into
your application documents (e.g. resume or cover letter), or emails to employers. It is
important that your personality shows - particularly in written documents. Make sure to
double-check any AI-written content included in your documents, ensuring it fits your style
and character.
Learning Activity

Click the link below to the online course, 'How to Boost your Productivity with AI tools' by
LinkedIn Learning. Please watch all videos included in the course. This course will take less
than 1 hour to complete - but go at your own pace!

https://www.linkedin.com/learning/how-to-boost-your-productivity-with-ai-tools

1. Gather your documents

One of the first steps before we can even begin a job search is to gather our essential
documents. For a professional job, this often includes the following:

- Curriculum Vitae

A CV or Resume is a one- to two-page document which demonstrates to an employer who

you are, your experience, and what you can offer their organization — in a clear, concise
manner. The resume is structured into different categories, with each category highlighting
specific information. CVs / Resumes usually include the following:

 Background/contact information: information at the beginning such as your first

name, last name, address, phone number and email address where applicable.

 Personal overview: a brief paragraph that gives the reader their first impression of
you. It should describe who you are professionally, what your interests are or goals
are, and any skills and achievements that make you stand out.

 Education history: This is helpful for employers who require certain educational and
experience levels. This section should include your most recent and relevant
education, such as your high-school diploma and any tertiary education.

 Employment history: Also known as the "professional history" section, this is an

opportunity to showcase the value you have brought to your former employees. You
should list down your most applicable work experiences in order, beginning with your
most recent job and what your roles and responsibilities were.

 Skills: This is where you would list all your strong skills (both technical and
interpersonal). Try to only list the key skills that make you stand out.

 Extracurricular activities: This section lists any other accomplishments or volunteer

work in the same structure as employment history. This helps to create a better
picture of who you are as an individual, further conveys your employability skills and
how willing you are to get involved with additional learning and community projects
beyond work.
- Cover Letter

A cover letter is a formal one-page document usually written for the hiring manager to
express why you want the role you're applying for, and why you would be suited to it. Cover
letters need to be tailored to each role you apply for, making sure to call out your passions,
dedication and interest in both the role and the overall firm you are applying to.

The structure of a cover letter is typically:

 Introductory paragraph: here, you explain why you are attracted to the position, the
particular organization and the field or industry. You should demonstrate your
research and understanding of the firm to spark the recruiter's interest. Even better if
you can link it to your interests and goals (as stated in your CV/resume).

 Middle paragraphs: why should you be chosen for the position? Focus on the top
three to five attributes listed in the job advertisement and provide specific examples
of where or how you have demonstrated them.

 Closing paragraph: Summarize what you can offer the organization. Finish the letter
with a positive attitude about your expectations — and thank them for the time and
opportunity — to leave a lasting and positive impression on the reader.

- Educational Transcripts
 References are usually one to two people who can vouch for your
character and endorse you for the role you're applying to.
References can come from university professors, previous
employers, senior members of an extracurricular/volunteer
organization, or anyone who can professionally endorse you (i.e.,
not your close friend or roommate).
 While references are usually required towards the final stages of the
job application process, it is wise to have some references ready to
go from the beginning.
 Most jobs typically request the contact details of your references so
that way they can contact the referee and have a verbal discussion
with them. Sometimes, it can be helpful to have written letters of
recommendation (written by your referees), which account for your
skills, accomplishments, and work ethic. These letters of
recommendation can be an advantageous boost to your application.

It is important to note that employees aren't the only ones utilizing AI in the job application
process. Many companies employ AI tools to review job applications and documents,
particularly in the early stages of the application. Because of this, it is important to pay close
attention to the job advertisement and match the terms/wording used in the advertisement.
For example, if the advertisement is looking for AI skills, you should make sure your CV or
cover letter directly discuss AI skills too.
2. Search, Search, Search

Great, you've got your documents organized - now begins the search.

Where can I search for jobs online?

See the table below for some of the major global websites used to search jobs.
Online Applications vs Networks

In the previous lesson, we discussed the advantages of having a professional network. This
refers to people you know, or reach out to, who work within a field or organization similar to
those you're interested in. A professional network offers many advantages - such as career
advice, insider knowledge, increased visibility within the industry and other forms of
support. Notably, professional networks can be a fantastic way to learn about job
opportunities not necessarily available to the rest of the public.

Survey

In a recent survey conducted by LinkedIn, the findings suggested that around 85% of all jobs
are filled via networking(opens in a new tab). So how do you network?

A great way to start is by creating an online profile using LinkedIn - a professional social
media platform that allows you to exhibit your skills and experience, meet new
professionals, form connections and learn about what's going on in your industry

3. Apply

Okay, you've done your research, you've searched for jobs, and now you've found a position
you like. Time to apply!

Online, the job application tends to be quite straightforward. Most sites will prompt you
through each stage, including where to submit your documentation. Some roles may
require you to answer specific questions about the role and yourself, so make sure to answer
these concisely and professionally in the same way you would when writing and cover letter.

4. Interview

Following your application being submitted, the remaining process often differs from
employer to employer. Assuming you get through to the next stage, you may need to go
through several series of interviews or screening to get to the point of a job offer.
Regardless, an interview is inevitable - so it's good to prepare!
The S.T.A.R. Method

A helpful rule of thumb when answering interview questions is to try and stay as concise as
possible. Your responses shouldn't take more than a minute at a time, so only mention
what's important!

The STAR method is an extremely helpful tool for interviews, particularly for situational
questions where you have to describe a time where you did something. This method helps
us to structure our answers in a way that is concise and engaging.

STAR stands for:

Using the STAR methods helps you to give well-structured, relevant and impactful interview
answers. It's always best to prepare, so try sitting down with a family member or a friend to
practice with, getting them to ask you some standard interview questions. Or, you could
leverage AI-powered tools to help you; for example, you can use ChatGPT to help
you research the company, structure questions and gain feedback on your answers. LinkedIn
offers a helpful tool - their Interview Preparation AI(opens in a new tab) - that can be
used to get instant feedback on interview answers in a more interactive way.

Video

Watch the short video below, "Top Interview Tips: Common Questions, Nonverbal
Communication & More" by Indeed (YouTube, 4:57 minutes) which provides some
guidelines for nailing that first interview.

Top Interview Tips: Common Questions, Nonverbal Communication & More | Indeed

Case studies: Job Opportunities

Below, let's take a look at a couple real-life job opportunities within the areas of
sustainability, business and entrepreneurship, and technology.
Key Points

1. 1

The job application process typically follows a series of steps from job application to job
acceptance.

2. 2

AI can be harnessed throughout the job application process to enhance your application and
preparation.

3. 3

In the job application process, it is important that you are able to accurately demonstrate
your skills, knowledge, experience and value, while also addressing the requirements and
responsibilities of the role.

4. 4

There are many ways to go about job searching, with benefits in networking as a way to gain
entry into a role or organization.

5. 5

It is important to prepare for interviews. The purpose of interviews is to see how you answer
questions and the behaviors you exhibit. We discussed the STAR method to structure
responses and the ways in which you can practice your interviews.

Congratulations!

You have reached the end of the EY Microsoft AI Skills Passport. Having completed the
General module, the Industry deep dives (Sustainability, Business and Entrepreneurship, and
Technology) and the Employability module, you many now click FINISH to receive your
certificate of completion!

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