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Internship Report - MACHINE LEARNING PROJECT

artificial intelligence (SRM Valliammai Engineering College)

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SRM VALLIAMMAI ENGINEERING COLLEGE

(An Autonomous Institution)
SRM Nagar, Kattankulathur, Chengalpattu Dt-603203, Tamil Nadu.

DEPARTMENT OF ARTIFICIAL INTELLIGENCE

& DATA SCIENCE
ACADEMIC YEAR: 2023-2024
REGULATION – 2019
REPORT
on

“1922709-INTERNSHIP”
at

FLSMIDTH PRIVATE LIMITED,EGATOOR

SUBMITTED BY
142221243013 – HARISH .V
SEVENTH SEMESTER
2023-2024 (Odd Semester)
BATCH: 2021-2025

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SRM VALLIAMMAI ENGINEERING COLLEGE

(An Autonomous Institution)
SRM Nagar, Kattankulathur – 603 203

DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE

CERTIFICATE

This is to certify that Mr. HARISH .V (Reg no. -142221243013) VII Semester,
B Tech Artificial Intelligence and Data Science has completed the Internship on
‘ARTIFICIAL INTELLIGENCE’ during the period 12th December 2023 to
26th December 2023 at Flsmidth Pvt Ltd, Egatoor , Chennai has submitted to
Anna University.

HEAD OF THE DEPARTMENT SIGNATURE

DEPT.OF ARTIFICIAL INTELLIGENCE NAME:
& DATA SCIENCE DESIGNATION:
SRM VALLIAMMAI ENGG.COLLEGE

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ACKNOWLEDGEMENT

I am highly indebted to Director Dr.B.Chidhambararajan, M.E., Ph.D. and

Principal Dr.M. Murugan, M.E., Ph.D.. and the Vice Principal
Dr.S.Visalakshi M.E.,Ph.D..for the facilities provided to accomplish this
internship.

I would like to thank my Head of the Department Dr. B. Muthu Senthil, B.E.,
M.E., Ph.D. Associate Professor for his constructive criticism throughout my
internship.

I would like to thank Mrs.R.Vaishnavi, B.Tech., M.Tech., Associate

Professor(O.G) and internship coordinator Department of AI&DS for her
support and advices to get and complete internship in above said organization.

I am extremely grateful to my department staff members and friends who

helped me in successful completion of this internship.

I would like to thank Mr.Shanmuga Chidambaram(Solution Architect) of

FLSMIDTH PVT LTD for giving me the opportunity to do an internship
within the organization.

I also would like to thank all the people that worked along with me in
FLSMIDTH PVT LTD for their patience and openness as they created an
enjoyable working environment.

It is indeed with a great sense of pleasure and immense sense of gratitude that I
acknowledge the help of these individuals.
HARISH .V

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(142221243013)

SRM VALLIAMMAI ENGINEERING COLLEGE

(An Autonomous Institution)
SRM Nagar, Kattankulathur – 603 203

DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE

VISION OF THE DEPARTMENT

To become a model for Artificial Intelligence with innovation and analysis for
higher learning through various analytical knowledge, creative competent and
dynamic technocrats; while remaining responsive to ethical, societal and
environmental issues.

MISSION OF THE DEPARTMENT

M1: To develop the students as an Artificial Intelligence designer and data

analyst professionals in order to meet the global design challenges and
entrepreneurs of international excellence as global leaders capable of
contributing towards technological innovations, learning process, participation
citizenship in their neighbourhood and economic growth.

M2: To transform value-based data science education to the students and groom
them as leaders in the field of Artificial Intelligence and Data Science for the
empowerment of society

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TABLE OF CONTENTS

SI . NO DESCRIPTION PAGE.NO
1. Introduction-About the Internship 1
2. Technology Learnt-Topic Covered 2
3. Details of project work carried out 10
4. Skills Learnt and Experience gained 15
5. Conclusion 17
6. Internship Certificate 18
ANNEXURE

i Permission Letter 19

ii About the Industry / Company Profile/ 20

address/ contact Person
iii Schedule copy 21

iv Sample Photos 22

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INTRODUCTION ABOUT INTERNSHIP

The Artificial Intelligence internship offers a robust blend of theoretical knowledge
and practical work experience, providing an in-depth introduction to creating and
improving AI-based systems. At the beginning of the internship, we focused on
understanding the fundamental concepts of Artificial Intelligence, covering topics such
as the history of AI, its evolution over the years, and its current state. This included
exploring the basic principles of AI, such as machine learning, deep learning, and
neural networks, and studying how AI systems are designed, how they function, and
the various types of AI, including narrow AI and general AI. After establishing a solid
foundation, we transitioned to more advanced topics, exploring various subfields of
AI, such as machine learning and robotics. We delved into understanding algorithms
and models, supervised and unsupervised learning, real-world applications like
predictive analytics and recommendation systems, and studied how machines
understand and interpret human language, applications in chatbots, translation
services, and sentiment analysis. We also learned how AI integrates with robotics to
create autonomous systems used in manufacturing, logistics, and even personal
assistants. We examined various real-world applications of AI, observing how these
technologies are transforming industries through case studies and projects involving
AI in customer insights and personalization. A significant highlight of the internship
was our hands-on training with Automation Anywhere, a leading platform for robotic
process automation (RPA). We learned to create bots to automate repetitive tasks,
deploy bots in real-world scenarios, and manage them using the Automation
Anywhere Community Edition software, ensuring they operate efficiently and
effectively. This experience provided us with practical skills in using AI tools and
platforms, highlighting the impact of automation in streamlining business processes,
reducing human error, and enhancing productivity.

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We also learned about the ethical considerations and potential challenges in AI
deployment, ensuring that we are mindful of these aspects in our future projects. We
engaged in capstone projects that allowed us to apply our knowledge and skills to real-
world problems, developing AI solutions for specific industry challenges, conducting
research, and presenting our findings to peers and mentors. By the end of the
internship, we had not only deepened our theoretical understanding of AI but also
gained substantial practical experience. This comprehensive learning journey has
equipped us with the knowledge and skills necessary to contribute effectively to AI
projects and initiatives in various sectors. The blend of foundational knowledge,
advanced learning, practical experience, and real-world application has been
instrumental in preparing us for a future in the dynamic field of Artificial Intelligence.

TECHNOLOGY LEARNT
MACHINE LEARNING
Machine learning (ML) is a subset of artificial intelligence that enables systems to
learn from data, identify patterns, and make decisions with minimal human intervention.
ML can be used to create bots that adapt and improve over time, handling complex tasks
such as predictions, classifications, and data analysis. For example, ML models can
enhance Optical Character Recognition (OCR) capabilities, allowing bots to accurately
extract text from scanned documents, images, and PDFs. Bots can leverage ML models
to analyze historical data and make predictions about future trends, such as sales
forecasts, customer behavior, and inventory management, and can identify unusual
patterns in data to detect fraud, errors, or other anomalies in real-time. Using ML, bots
can classify and categorize data, such as sorting customer inquiries by type, prioritizing
tasks, and routing documents to the appropriate departments. Additionally,
recommendation systems.

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by ML can provide personalized suggestions based on user behavior and preferences.
Intelligent task automation allows bots to handle more complex tasks that require
understanding context, learning from new data, and making decisions without explicit
programming for every scenario. Bots can improve their performance over time by
learning from feedback and new data, adapting to changing conditions and
requirements. Tools like Automation Anywhere IQ Bot, which leverages AI and ML to
handle unstructured data, and machine learning frameworks like TensorFlow, PyTorch,
and Scikit-Learn, can be integrated to create advanced and customized ML models.
Cloud-based AI services from providers like AWS, Microsoft Azure, and Google Cloud
can simplify the deployment and scaling of ML models. Integrating ML with RPA
increases accuracy, efficiency, scalability, and adaptability, allowing bots to handle a
wide range of complex tasks autonomously, reducing the need for human intervention
and driving greater innovation in automation projects.

ARTIFICIAL INELLIGENCE
Artificial Intelligence (AI) refers to the simulation of human intelligence in
machines that are designed to think, learn, and perform tasks that typically require
human intelligence. It is a broad and interdisciplinary field that combines computer
science, mathematics, statistics, cognitive science, and other disciplines.AI aims to
develop intelligent systems that can perceive, understand, reason, learn, and interact
with the environment. These systems can analyse vast amounts of data, recognize
patterns, make decisions, and solve complex problems with efficiency and accuracy.
The ultimate goal of AI is to create machines that can mimic and replicate human
intelligence across various domains.

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There are two main categories of AI: Narrow AI (also known as weak AI) and General
AI (also known as strong AI). Narrow AI refers to AI systems that are designed for
specific tasks and have limited capabilities within a specific domain. Examples include
voice assistants, recommendation systems, and image recognition software. General AI,
on the other hand, refers to AI systems that possess the ability to understand, learn, and
apply knowledge across different domains, similar to human intelligence. General AI
aims to exhibit human-like intelligence and adaptability.AI techniques encompass
various subfields, including machine learning, deep learning, natural language
processing, computer vision, robotics, and more. Machine learning algorithms enable AI
systems to learn from data and make predictions or decisions without being explicitly
programmed.

ROBOTIC PROCESS AUTOMATION

Robotic Process Automation (RPA) involves using software robots or "bots" to
automate highly repetitive, routine tasks that are typically performed by humans.
These tasks can range from simple operations, such as copying and pasting data, to
more complex processes that involve multiple steps and decision points. By
automating these tasks, organizations can improve efficiency, reduce errors, and free
up human workers to focus on more strategic activities. RPA platforms, such as
Automation Anywhere, UI Path, and Blue Prism, offer tools and features that make it
easy to design, deploy, and manage these bots. These platforms provide intuitive
interfaces and robust functionalities to facilitate the creation of automation workflows.

Automation Anywhere is renowned for its user-friendly environment and advanced

capabilities, making it accessible to both beginners and experienced professionals. It
supports a wide range of automation tasks, from data entry and form filling to more

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sophisticated processes like document processing and data analysis. UI Path, another
popular RPA tool, offers a similarly user-friendly interface with a focus on ease of use
and scalability. It includes comprehensive features for process design, workflow
automation, and advanced analytics, enabling users to automate a wide range of
business processes. Blue Prism is another leading RPA platform known for its
enterprise-grade features and strong focus on governance and security. By mastering
multiple RPA platforms like Automation Anywhere, UI Path, and Blue Prism,
professionals can enhance their versatility and ability to deliver effective automation
solutions across various industries. The integration of RPA with other technologies
further expands its potential. Combining RPA with artificial intelligence (AI) and
machine learning (ML) enables bots to handle more complex tasks that require
decision-making, pattern recognition, and predictive analytics.

MICROSOFT BOT FRAMEWORK

The Microsoft Bot Framework is a comprehensive platform for building,
connecting, testing, and deploying intelligent bots that can interact naturally with users
on various channels. By integrating the Microsoft Bot Framework with the
Automation Anywhere platform, you can enhance your automation solutions by
adding conversational capabilities, enabling bots to interact with users in a more
intuitive and user-friendly manner. Integration with Automation Anywhere can be
achieved through APIs and webhooks, allowing the conversational bots built with the
Microsoft Bot Framework to trigger and interact with RPA bots. For instance, a
customer service bot could collect information from a user through a chat interface and
then trigger an Automation Anywhere bot to process a request, update records, or
perform other back-

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end operations. This seamless integration enhances the overall automation workflow,
providing a unified solution that combines the strengths of conversational AI and RPA.
In addition to these features, the Microsoft Bot Framework integrates with various
other Azure services to provide additional capabilities. For instance, integrating with
Azure Bot Service allows you to deploy and scale your bots on Azure infrastructure,
ensuring high availability and performance. You can also leverage Azure's analytics
services to monitor bot interactions, gather insights, and continuously improve the
bot's performance.By leveraging the Microsoft Bot Framework in conjunction with
Automation Anywhere, you can create sophisticated, intelligent bots that not only
automate routine tasks but also provide a natural and engaging user interface. This
combination of technologies enables you to build comprehensive automation solutions
that can handle a wide range of tasks and processes across various industries and
applications, ultimately driving greater efficiency and user satisfaction.

DIALOG FLOW
Dialogflow, developed by Google, is a robust tool for creating conversational
interfaces like chatbots and voice applications, and integrating it with the Automation
Anywhere platform can significantly enhance automation capabilities. Dialogflow uses
natural language processing (NLP) to understand and process human language,
enabling bots to handle text and voice inputs in a more intuitive manner. By defining
intents, training phrases, and entities, Dialogflow allows you to create bots that can
accurately interpret user inputs and maintain conversational context.When integrated
with Automation Anywhere, Dialogflow can trigger automation tasks through
webhooks and

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APIs. For example, Dialogflow can send a webhook request to an endpoint where an
Automation Anywhere bot is listening, using extracted user input parameters to
perform specific tasks. This integration allows for sophisticated interactions where
bots can handle both structured automation tasks and unstructured conversational
inputs. Dialogflow’s fulfillment capabilities enable bots to interact with external
systems, facilitating tasks like generating reports or processing customer requests. By
leveraging this integration, you can create intelligent bots that offer a seamless user
experience, automate routine processes, and enhance overall efficiency across various
applications and industries.

Additionally, integrating Dialogflow with Automation Anywhere opens up

opportunities for advanced conversational scenarios and dynamic interactions. For
instance, Dialogflow’s ability to manage context and handle multi-turn conversations
allows for more engaging and effective user interactions. Automation Anywhere bots
can utilize Dialogflow’s insights to make informed decisions and execute complex
workflows based on real-time user inputs. This combination not only streamlines
business processes but also provides users with a more personalized and responsive
experience. The synergy between Dialogflow’s conversational AI and Automation
Anywhere’s automation capabilities creates a powerful toolset for addressing diverse
needs, from customer service to operational efficiency, ultimately driving innovation
and enhancing overall business performance.

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LIBRARIES USED
AUTOMATION ANYWHERE BOT
The Automation Anywhere platform provides a range of bot libraries and tools that
enhance automation capabilities through the Automation Anywhere Bot Store and IQ
Bot Libraries.

Automation Anywhere Bot Store is a comprehensive repository where users can

access a wide array of pre-built bots and bot templates. This store is designed to
facilitate the quick deployment and customization of bots by providing ready-to-use
solutions that cover various automation scenarios. The bots available in the Bot Store
often come with built-in libraries and scripts tailored for specific tasks or integrations,
making it easier for users to implement complex functionalities without starting from
scratch. These pre-built bots can handle tasks such as data extraction, process
automation, and integration with other systems, and they serve as a valuable resource
for accelerating automation projects and reducing development time.

IQ Bot Libraries are specialized libraries used within the IQ Bot framework,
which is part of the Automation Anywhere platform focused on intelligent document
processing. IQ Bot utilizes advanced technologies like Optical Character Recognition
(OCR) and Natural Language Processing (NLP) to extract and interpret data from
unstructured documents, such as invoices, emails, and forms. The libraries within IQ
Bot include sophisticated algorithms and models for text recognition, data extraction,
and language understanding, enabling bots to process and analyze documents with

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high accuracy. These libraries help automate tasks that involve handling and
interpreting

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large volumes of unstructured data, making them essential for workflows that require
data extraction from diverse sources.
Together, the Automation Anywhere Bot Store and IQ Bot Libraries provide a
robust set of tools and resources for developing, deploying, and enhancing automation
solutions, enabling users to create efficient and intelligent bots that can tackle a wide
range of business processes.

PROGRAMMING AND SCRIPTING

In the Automation Anywhere platform, programming and scripting libraries play a
crucial role in enhancing the functionality and flexibility of bots. The platform
supports integration with both Python and JavaScript, allowing developers to leverage
a variety of libraries to extend bot capabilities.

Python Libraries are extensively used within Automation Anywhere bots to

perform complex tasks and data processing. Libraries such as `pandas` and `numpy`
are particularly valuable for data manipulation and analysis. Additionally, the
`requests` library is used for making HTTP requests, allowing bots to interact with
web APIs, retrieve data from online sources, and submit information to external
services. These libraries enable bots to execute a wide range of tasks, from data
extraction and transformation to complex analytical processes.

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JavaScript Libraries are utilized for web automation tasks, providing tools to
interact with web elements and manage web-based workflows. Libraries like `jQuery`
simplify the process of manipulating HTML documents and handling events, making it
easier to automate interactions with web pages.

DETAILS OF PROJECT WORK CARRIED OUT

TOPIC: CREATION OF AN “GMAIL LOGIN” BOT

INTRODUCTION:
Using the Automation Anywhere platform's extensive toolkit to plan,
develop, and oversee automated processes is necessary for creating a bot. Automation
Anywhere is a platform that enhances business operations by fusing cognitive
automation components like machine learning and artificial intelligence (ML) with
classical robotic process automation (RPA). First, the tasks that need to be automated
are identified. Next, the Automation Anywhere Bot Creator's drag-and-drop interface
is used to construct the bot. After it is designed, the bot is developed by specifying the
steps it will take to complete tasks like data entry, interacting with applications, and
making decisions.

The bot is put through extensive testing after development to make sure it is
accurate and effective. The bot is deployed via the Automation Anywhere Control
Room after testing is complete, allowing for scheduling, managing, and monitoring.
To guarantee that the bot runs properly and adjusts to any changes in business
processes, ongoing maintenance and monitoring are necessary. Through the
automation of repetitive operations, organisations can attain greater productivity and

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drive digital transformation by reducing errors, increasing efficiency, saving money,

and improving compliance.

Steps to Create a Bot

1. Planning: Identify the process to be automated. Analyze the steps involved,
the data required, and the expected outcome.
2. Design: Use Automation Anywhere Bot Creator to design the workflow.
This involves defining the sequence of actions the bot will perform.
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3. Development: Develop the bot by dragging and dropping commands, such
as opening applications, reading/writing data, and interacting with user interfaces.
4. Testing: Test the bot in a controlled environment to ensure it performs the
desired tasks accurately and efficiently.
5. Deployment: Deploy the bot using Automation Anywhere Control Room.
Set up schedules, manage permissions, and monitor the bot’s performance.

PROJECT REQUIREMENTS
HADWARE REQUIREMENTS
1. Operating System-Windows 11
2. Processor-Intel Core i5 and above
3. RAM-8GB
4. SSD-520GB

SOFTWARE REQUIREMENTS

1. Language Used: Automation Anywhere's Proprietary Scripting Language,

SQL, APIs,Python
2. Operating System: Windows 11
3. Libraries: Pandas, NumPy, Node.js, Axios

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BENEFITS
 Increased Efficiency: Bots can work 24/7 without breaks, significantly
speeding up processes.
 Reduced Errors: Automating repetitive tasks minimizes human error,
ensuring higher accuracy.
 Cost Savings: Automation reduces the need for manual labor, leading to
cost savings.
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 Scalability: Automation Anywhere allows for the easy scaling of operations
as business needs grow.
 Improved Compliance: Bots can be programmed to follow compliance
regulations strictly, reducing the risk of non-compliance

ABOUT THE WORKFLOW

To create a Gmail login bot using Automation Anywhere, start by opening the
Automation Anywhere client and creating a new task. Use the "Open Browser"
command to navigate to `https://mail.google.com` and add a "Wait" command
to ensure the page loads fully. Next, use the "Set Text" command to enter the
email address in the input field, followed by the "Click" command to press the
"Next" button. Add another "Wait" command for the password page to load,
then use "Set Text" to enter the password and "Click" to press "Next" again.
Once the inbox page loads, use a final "Wait" command to ensure it is fully
loaded. To verify the login, use an "If/Else" command to check for a specific
element unique to the inbox. If successful, proceed; if not, handle the error by
logging it, taking a screenshot, or retrying the login with the "On Error"
command. Finally, close the browser with the "Close Browser" command and
end the task with the "End" command. This workflow ensures a systematic and
efficient Gmail login process using Automation Anywhere.

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WORKFLOW OF THE BOT

Step 1: Create a New Task
1. Open Automation Anywhere Client.
2. Create a New Task:
- Go to `File` > `New` > `Task`.

Step 2: Open Gmail Login Page

1. Open Browser:
- Command: `Open Browser`
- URL: `https://mail.google.com`
- Browser: Choose your preferred browser (e.g., Chrome).

Step 3: Wait for Page to Load

1. Wait:
- Command: `Wait`
- Condition: `Wait for Window`
- Window Title: Specify the title of the Gmail login page (e.g., "Gmail").
- Timeout: Set an appropriate timeout (e.g., 10 seconds).

Step 4: Enter Email Address

1. Set Text:

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- Command: `Set Text`

- Window Title: Specify the title of the Gmail login page.
- Object Properties: Identify the email input field.
- Value: Your email address (use a variable for security).

2. Click Next:
- Command: `Click`
- Window Title: Specify the title of the Gmail login page.
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- Object Properties: Identify the 'Next' button.

Step 5: Wait for Password Page to Load

1. Wait:
- Command: `Wait`
- Condition: `Wait for Window`
- Window Title: Specify the title of the Gmail password page.
- Timeout: Set an appropriate timeout (e.g., 10 seconds).

Step 6: Enter Password

1. Set Text:
- Command: `Set Text`
- Window Title: Specify the title of the Gmail password page.
- Object Properties: Identify the password input field.
- Value: Your password (use a variable for security).

2. Click Next:
- Command: `Click`
- Window Title: Specify the title of the Gmail password page.
- Object Properties: Identify the 'Next' button.

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Step 7: Wait for Inbox to Load

1. Wait:
- Command: `Wait`
- Condition: `Wait for Window`
- Window Title: Specify the title of the Gmail inbox page.
- Timeout: Set an appropriate timeout (e.g., 10 seconds).

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Step 8: Verify Login
1. If/Else:
- Command: `If/Else`
- Condition: `If Window Exists`
- Window Title: Specify an element or title unique to the Gmail inbox page
(e.g., "Inbox - your-email@gmail.com").
- If True: Proceed to next steps.
- If False: Handle login failure (e.g., take a screenshot, log the error, or retry).

Step 9: Error Handling

1. Error Handling:
- Command: `On Error`
- Action: Define actions for error handling.
- Options: Log the error, take a screenshot, send an alert, or retry.

Step 10: Close Browser

1. Close Browser:
- Command: `Close Browser`
- Browser: Choose your preferred browser (e.g., Chrome).

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Step 11: End Task

1. End:
- Command: `End`

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OUTPUT

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SKILLS LEARNT
Artificial Intelligence:
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines
that are programmed to think and perform tasks typically requiring human intelligence.

Machine Learning: Machine learning focuses on developing algorithms and statistical

models that enable computers to learn from data and make predictions or decisions
without being explicitly programmed.

Deep Learning: Deep learning is a subfield of machine learning and artificial

intelligence that focuses on building and training artificial neural networks to mimic the
way the human brain processes information.

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Natural Language Processing (NLP): NLP focuses on enabling computers to

understand, interpret, and generate human language. It involves tasks such as speech
recognition, sentiment analysis, machine translation, text summarization, and question-
answering systems.

Computer Vision: Computer vision is a field of artificial intelligence and computer

science that focuses on enabling computers to interpret and understand visual
information from the world.

Data Analysis: Data analysis is the process of inspecting, cleaning, transforming, and
interpreting data to discover meaningful insights, draw conclusions, and support
decision-making. It involves using various statistical and computational techniques to
explore and make sense of large datasets.

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EXPERIENCE GAINED
RPA Design and Development: By working with automation anywhere platform I
gained proficiency in using pre-built commands for various automation tasks such as
file operations, data handling, and system controls.By working with the Automation
Anywhere platform, I gained proficiency in using pre-built commands for various
automation tasks such as file operations, data handling, and system controls.

Data Handling and Manipulation: I have learnt how to extract data from various
sources such as files, databases, and web applications and I have gained experience in
transforming and processing data. Additionally, I have developed skills in integrating
and consolidating data from multiple sources to create comprehensive datasets, which
support detailed analysis and reporting, ensuring data consistency and reliability across
different systems

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Practical application Development: This commonsense application improvement

assists with applying the programming abilities to construct a practical application. This
incorporates errands, for example, examining report utilizing artificial intelligence
module. It gives a viable comprehension of building intelligent applications that join
various innovations and convey a consistent client experience.

Interpersonal Skills: Being an effective designer having solid relational abilities is

important on the grounds that this occupation much of the time includes drawing in with
clients and colleagues. You ought to project a certain disposition and display areas of
strength for a ethic. In the event that you coexist with individuals well, you'll speak with
your collaborators also, clients really and satisfy your capability as well as could be
expected.

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CONCLUSION
My internship at FLSmidth was an exceptionally enriching experience that provided me
with a deep understanding of creating bots using the Automation Anywhere platform.
During my time there, I was immersed in the practical aspects of Robotic Process
Automation (RPA), working hands-on with the Automation Anywhere tools and
methodologies.

Using the platform's user-friendly interface—which has a drag-and-drop feature for

building intricate workflows—I learnt how to create and develop bots. Through this
training, I was able to become proficient in using a variety of built-in commands to
automate tasks including handling files, analysing data, and running systems.
Additionally, I developed my skills in custom scripting, utilising Python and JavaScript.

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During the internship, I worked on developing and testing bots as well as managing and
deploying them using the Automation Anywhere Control Room. I gained knowledge on
how to manage exceptions, set up bot schedules, and guarantee safe and legal
automation procedures. Working on actual projects also gave me the chance to better
grasp how automation can be strategically applied to enhance corporate operations and
boost productivity.

Everything considered, my internship at FLSmidth helped me improve my RPA skills

and gave me practical knowledge about how to use Automation Anywhere to create
scalable and efficient automation solutions. I also learnt a lot about automating
operations and troubleshooting them, which improved my ability to solve problems in
practical situations.

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INTERNSHIP CERTIFICATE

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ANNEXURE

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PERMISSION LETTER

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ABOUT THE INDUSTRY / COMPANY PROFILE / ADDRESS /

CONTACT

CONTACT DETAILS
FLSMIDTH PRIVATE LIMITED
"FLSMIDTH HOUSE" 34, EGATOOR, RAJIV GANDHI SALAI,
KELAMBAKKAM - 603103
Tamil Nadu – India

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SCHEDULE COPY

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DATE DAY TOPICS

12-12-2023 1 Introduction
13-12-2023 2 How AI process works?
14-12-2023 3 Introduction to RPA and Automation
Anywhere
15-12-2023 4 Basic Bot Creation
16-12-2023 5 File Operations
17-12-2023 6 Data Handling and Manipulation
18-12-2023 7 Working with Databases
19-12-2023 8 System Controls and Automation
20-12-2023 9 Web Automation
21-12-2023 10 Bot Deployment and Scheduling
22-12-2023 11 Application,email Automtation
23-12-2023 12 Using Loops and Conditional
Statements
24-12-2023 13 Project Planning and Specification
25-12-2023 14 Project-Execution and Evaluation
26-12-2023 15 Project Demo

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SAMPLE PHOTOS

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