Prompt Engineer Course Program
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ScribdTranslationsPrompt Engineer Course Program
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ScribdTranslationsProgram of
Prompt Course
Engineer
Module 1: Introduction to Creation
Prompts
What is a prompt?
2. Differences between a good and a bad prompt
3. Where can we use prompts?
4. Super Powerful Tools to Speed Up Your Daily Work
A day with Artificial Intelligence
5. Creating your own Portfolio with AI
6. Use the full power of generative Artificial Intelligence to
generate benefits
Module 2: Design and Types of Prompts
1. Types of texts generated by ChatGPT
2. Previous prompts to prepare ChatGPT
3. Open, closed, and multiple prompts
4. Instruction or content generation prompts
5. Analysis or review prompts
6. Sequential prompts
7. Personality Analysis Prompts
8. Negative prompts
9. Example of a good prompt
Module 3: Tools and tricks for creating
best prompts
1. Tricks to generate good Prompts
2. Automatic Prompts without typing with AIPRM
3. Respond to emails with ChatGPT
4. Earning money by selling your Prompts (Bonus)
5. 7 ideas to make money with ChatGPT
Module 4: Prompts for functionalities
concrete
1. Prompts to help you Make Money Online
1-click posts better than your competition
3. Create Online Courses with ChatGPT
4. Create images with Prompts
5. Prompts to write a book with ChatGPT
Module 5: Prompts for Images and Videos
1. Introduction to Image Generation with AI
2. Introduction to Stable Diffusion and Midjourney
3. Midjourney: an innovative approach
4. Stable Diffusion in detail
5. Real applications of generative image AI
6. Create videos with Artificial Intelligence
Module 1: Introduction to Creation
Prompts
What is a prompt?
A prompt is an instruction or initial phrase used to guide generation.
text in a language model. It is the input text provided to the model
to obtain a coherent response or continuation. The prompts may vary in
length, from a single word to complete paragraphs, depending on the task and the
complexity of the context that is desired to be established.
A prompt can be a question, a statement, a request for information or
any other form of interaction with the language model. For example, in the
context of a chatbot, the prompt could be 'Hello, how can I help you today?' or
Tell me more about your travel preferences.
2. Differences between a good and a bad prompt
A good prompt is one that successfully guides the language model to obtain a
appropriate and coherent response to expectations. Some characteristics of a good
prompt include:
Clarity and conciseness: The prompt must be clear and unambiguous to avoid
incorrect or confusing answers.
Sufficient context: Provide enough contextual information for the
The model understands the intention behind the prompt and can generate a response.
relevant.
Specificity: A specific prompt helps the model generate more responses.
precise. Instead of asking 'How is the weather?', a more
specifically could be "What is the current temperature in New York?"
Coherence and consistency: The prompt must be consistent with the style and tone of the
expected dialogue consistent with previous interactions.
On the other hand, a bad prompt can lead to inadequate or incoherent responses.
Some characteristics of a bad prompt are:
Ambiguity: An ambiguous prompt can confuse the model and generate
incorrect or irrelevant answers.
Lack of context: If the prompt does not provide enough information about
In context, the model may generate generic or out-of-context responses.
Bias or prejudice: A prompt that contains biases or prejudices can influence
the model's responses and generate undesirable results.
3)Where can we use prompts?
Prompts are used in a wide range of applications and contexts. Some
examples include:
Chatbots and virtual assistants: Prompts are used to interact with the
users and generate real-time responses in chatbot applications and
virtual assistants.
Creative text generation: Prompts are used to stimulate the
creativity in the generation of literary texts, such as stories, poems or
songs.
Automatic translation: Prompts can serve as source text for the
automatic translation, where the model generates the corresponding translation in
another language.
Automatic summary: Prompts are used to summarize text, where the
model generates a concise and relevant summary based on the information
provided in the prompt.
Code generation: In programming, prompts can be used to
generate automated code based on requests and requirements
provided.
In summary, prompts are widely used in various applications that
involves the generation of automatic text. Its proper formulation and use
are fundamental for obtaining precise and coherent results.
4) Super Powerful Tools to accelerate your daily work with
Artificial Intelligence
In this topic, various tools and resources that can help will be explored.
accelerate daily work with artificial intelligence in the field of Prompt Engineering.
Some of these tools include:
Chatbot development platforms: There are various platforms that facilitate
the creation and management of chatbots, providing visual interfaces,
integrations with external services and model training capabilities
of language.
NLP libraries and frameworks: Libraries and frameworks can be used
of natural language processing (NLP) like NLTK, spaCy or
Transformers for performing preprocessing tasks, linguistic analysis and
text generation.
Data annotation tools: To train language models and
improving the quality of prompts requires having data sets
annotated. Tools like Prodigy or Label Studio allow for annotation
data efficient for training and validation.
Collaboration and project versioning platforms: Use tools
how GitHub, GitLab, or Bitbucket facilitates team collaboration, control
of versions and project management of Prompt Engineering.
5) Creating your own Portfolio with AI
This topic focuses on the creation of a personalized portfolio to showcase
projects and skills in the field of artificial intelligence. Some aspects to
consider including:
Selection of highlighted projects: Select projects that demonstrate your
skills in creating and managing prompts. They can be projects in which
you have previously worked on or personal projects that you have developed
to showcase your abilities.
Project documentation: Create detailed documentation for each
project, explaining the objective, the challenges, the methods used and the
obtained results. Includes examples of prompts and shows how you improved the
text generation throughout the project.
Visual presentation: Make sure to present your projects in a visually
attractive. Use images, graphics, and screenshots to illustrate the
results and the process of creating prompts.
Interactive demonstrations: If possible, include interactive demonstrations
of your projects in operation. You can create prototypes of chatbots or
virtual assistants that show how your prompts work in real time.
Links to source code: If the projects are code-based, provide
links to the corresponding repository for potential employers or
collaborators can review your work in detail.
6) Use all the power of generative Artificial Intelligence to generate
benefits
This topic focuses on the application of generative artificial intelligence techniques to
generate benefits in different areas. Some areas of application could be:
Automated content generation: Explore how to use techniques of
text generation for creating automated content, such as descriptions of
products, news, stories or answers to frequently asked questions.
Personalization of recommendations: Examine how generative models
they can adapt to the individual preferences and characteristics of the users
to provide more personalized recommendations in fields such as commerce
electronic, entertainment, or advertising.
Automation of repetitive tasks: Shows how artificial intelligence
generative can be used to automate repetitive tasks that require the
text generation, such as customer service, report writing or
standard email reply.
Productivity Improvement: Explore how generative models can
help professionals be more productive by generating drafts,
summaries or creative ideas in different fields, such as writing, design or
strategic planning.
In summary, these intermediate/advanced topics within the introduction module to
Prompt Engineering will allow students to explore powerful tools,
develop your own portfolio with AI projects and understand how to use the
generative artificial intelligence to obtain benefits in various fields.