Generative AI Course

Introduction to Generative AI Prompt Engineering Building AI-Powered Websites Creating an ML Project Prompt Examples Writing a Book with AI

Chapter 1: Foundations of Generative AI with ChatGPT

Introduction to Generative AI and ChatGPT

Welcome to the world of Generative AI. In this course, we’ll explore the basics of Generative AI and how it’s transforming industries.

Generative AI refers to algorithms, like ChatGPT, capable of creating new content based on the data they’ve been trained on. From text and code to images, audio, and video, generative AI models open up new possibilities for automation, creativity, and insights across various domains.

Generative AI, particularly through models like ChatGPT, is transforming various fields by enabling machines to generate content that feels remarkably human-like. Generative AI models are trained on vast datasets and can produce text, images, and more by understanding patterns in data.

Motivations and Potential: From Idea to Impact

Generative AI holds the potential to revolutionize industries by automating content creation, enhancing customer service, and generating data-driven insights. As you embark on this journey, envision how your skills in generative AI could make an impact on fields ranging from customer service chatbots to AI-generated art and automated code generation.

Learning Objectives

Example Prompts

User
"What are some practical applications of generative AI in business?"
Chatbot
"Generative AI is widely used in content creation, personalized recommendations, and customer support. For example, it can generate product descriptions, answer customer queries, and suggest content based on user preferences."
User
"How does generative AI differ from traditional AI?"
Chatbot
"Traditional AI often classifies or predicts based on existing data, while generative AI creates new data. For example, it can generate realistic images, write articles, or simulate conversations."

Chapter 2: Prompt Engineering Basics for Beginners

1. 🎯 Introduction to Prompt Engineering for Websites and AI Projects

Effective prompt engineering is essential for creating interactive website features and generating clear AI/ML project documentation. A well-crafted prompt can enhance user engagement on a portfolio website and make AI project insights more accessible.

Example Comparison

Basic Prompt: "Write an ‘About Me’ section."

ChatGPT Response: "I'm a data scientist who works with data and machine learning."

Refined Prompt: "Write a professional ‘About Me’ section for a data scientist with 5 years of experience in NLP and ML, focusing on key achievements and technical expertise."

Chatbot
"ChatGPT Response: ""I am an experienced Data Scientist with 5 years specializing in Natural Language Processing (NLP) and Machine Learning. I have successfully developed predictive models and NLP solutions, significantly improving process efficiency and customer insights across multiple projects. My technical expertise includes Python, TensorFlow, Scikit-Learn, and SQL, and I am passionate about translating complex data into meaningful, actionable results."

🔑 Key Insight:

Clarity and specificity improve the quality and relevance of responses, making your content more professional and tailored to your audience.

2. 🏢 Concept Explanation: Qualities of an Effective Prompt

Crafting an effective prompt requires attention to clarity, specificity, and tone. Here are key elements to focus on:

  • Clarity: Clear prompts yield precise answers. Avoid ambiguity by being direct.
  • Specificity: Use detailed keywords to guide the response.
  • Tone: Set the tone for a professional or casual response as needed.
Example: Annotated Prompt Comparison

Generic Prompt: "Describe my skills."

Specific Prompt: "Describe my top three skills as a data scientist, with examples from past projects."

🔑Key InsightRefining the prompt made a significant difference in the response. While the initial prompt gave a very generic answer, the refined prompt resulted in a more detailed, professional response that highlights specific skills, experience, and impact.s.

3. 🛠️ Hands-On Example 1: Crafting Prompts for a Portfolio Website Chatbot

This example walks you through creating prompts for a chatbot on a portfolio website.

User Prompt: "Explain my top three technical skills as a data scientist."
ChatGPT Response: "Your top three skills as a data scientist include machine learning, data preprocessing, and NLP, showcasing your ability to analyze complex data."
Refined Prompt: "List my top three data science skills with specific project examples."
ChatGPT Response: "Your top three data science skills are: 1) Machine Learning (developed a sales forecasting model), 2) Data Preprocessing (cleaned large datasets for analysis), 3) NLP (created a chatbot using NLP techniques)."

🔑 Refinement Steps: Each revision of the prompt adds clarity and relevance to the chatbot interaction, making it more engaging and informative for website visitors.

4. 🛠️ Hands-On Example 2: Crafting Prompts for AI/ML Project Documentation

This example demonstrates how to create prompts that help document your AI/ML project effectively.

User Prompt: "Summarize the performance of my regression model on housing data."
ChatGPT Response: "The model achieved high accuracy with key variables like size and location, helping predict housing prices precisely."
Refined Prompt: "Summarize my regression model’s results in a way suitable for a non-technical audience."
ChatGPT Response: "Our model accurately predicts home prices by considering size, location, and number of rooms. It provides useful insights for homeowners making investment decisions."

5. Practice Exercises

🎯 Portfolio Task: "Write a project summary focusing on impact and results for a deep learning project."

💡 Expected Output: "Developed a deep learning model for image classification with 98% accuracy, enabling faster image data categorization."

🎯 AI/ML Task: "Generate a user-friendly explanation of model accuracy for a non-technical audience."

💡 Expected Output: "Our model predicts outcomes with high accuracy, making it a reliable tool for decision-making."

6. Summary and Key Takeaways

  • 🔑 Prompt Refinement: Refining prompts improves response quality and relevance.
  • 💡 Practical Applications: Effective prompts are invaluable for creating engaging portfolio content and clear project documentation.

Prompt Engineering for Beginners

Essentials of Prompt Crafting

Prompt engineering is the art of crafting questions and instructions to get precise answers from AI. Clear instructions often yield the most relevant outputs from ChatGPT. Here’s a breakdown of effective prompt techniques:

  • Be Specific: Provide detailed instructions to get the exact response you need.
  • Define Roles: Ask the model to act as a particular expert, like “You are a data analyst…”
  • Limit Output Length: Specify word count or bullet points if you need concise answers.

Visual: Step-by-Step Prompt Engineering Process

Prompt engineering is an iterative process. It's essential to experiment with different ideas and test the AI prompts to see the results. You may need multiple tries to optimize for accuracy and relevance. Continuous testing and iteration reduce the prompt size and help the model generate better output.

Chatbot

“Specify the goal,” “Use clear instructions,” and “Test responses”

Building a Chatbot for Your Portfolio Website

Imagine integrating a chatbot powered by ChatGPT into your website portfolio. Not only does this add interactivity, but it also showcases your ability to work with AI tools. Here’s a sample code to get you started on building a simple chatbot:


<!-- Sample HTML structure for a simple chatbot -->
<div id="chatbot">
    <div id="chatbox"></div>
    <input type="text" id="userInput" placeholder="Type a message..." />
    <button onclick="sendMessage()">Send</button>
</div>

<script>
    function sendMessage() {
        const userInput = document.getElementById("userInput").value;
        const chatbox = document.getElementById("chatbox");
        chatbox.innerHTML += "<p>User: " + userInput + "</p>";
        // Simulate ChatGPT response
        chatbox.innerHTML += "<p>ChatGPT: Hello! How can I help you?</p>";
    }
</script>

Building a Chatbot

Here’s an example of a simple chatbot interface using HTML and JavaScript:

Chapter 3: Building an AI-Powered Portfolio Website

Introduction: Learn how to use ChatGPT to build a personalized portfolio website, complete with design, layout, and interactive features.

Discover how to use AI tools to create portfolio websites with interactive elements.

Core HTML/CSS components and how ChatGPT can generate initial structures and designs.

ChatGPT: "Generative AI can assist in creating, designing, and updating websites by generating code and content based on prompts."

My Portfolio

Hands-On Example: Creating a Portfolio Layout

🎯 Goal: Create a modern layout with sections for projects, skills, and contact information.

Chatbot

“Define your prompt. Then re-define”

Student: “Create HTML and CSS code for a header with a navigation menu (Home, About, Projects, Contact).”

ChatGPT: 


                    
                    <header>
                        <nav>
                            <ul>
                                <li><a href="#home">Home</a></li>
                                <li><a href="#about">About</a></li>
                                <li><a href="#projects">Projects</a></li>
                                <li><a href="#contact">Contact</a></li>
                            </ul>
                        </nav>
                    </header>

Styled Portfolio

4. How to Ask for Changes and Refinements

🔑 Key Insight: Refine your website by requesting changes to styling, layout, or content based on initial feedback.

Refine your website by requesting changes to styling, layout, or content based on feedback.

Student: “Modify the 'About Me' section to use a professional tone and add a list of skills.”

ChatGPT: 

                    <!-- HTML Code for About Me Section -->
                    <section id="about">
                        <p>I’m a data scientist with expertise in machine learning, data visualization, and NLP. Skilled in Python, R, and SQL.</p>
                        <ul>
                            <li>Machine Learning</li>
                            <li>Data Visualization</li>
                            <li>Natural Language Processing</li>
                        </ul>
                    </section>

I’m a data scientist with expertise in machine learning, data visualization, and NLP. Skilled in Python, R, and SQL.

  • Machine Learning
  • Data Visualization
  • Natural Language Processing

5. Practice Exercises

  • 💡 Exercise: Create a "Skills" section with a list of key technical skills.
  • 🎯 Exercise: Customize the background color of the "About Me" section.

6. Summary and Key Takeaways

🔑 Recap: We’ve covered the essentials of creating a portfolio website using HTML, CSS, and ChatGPT.

  • Use ChatGPT to create and refine HTML/CSS for your portfolio.
  • Customize each section based on your brand.
  • Practice modifying prompts to adjust website features easily.

Chapter 4:Building a Multi-Feature AI/ML Project with ChatGPT

This module walks you through building a machine learning project from start to finish.

1. Introduction to AI/ML Project Development

This chapter will guide you through creating a comprehensive AI/ML project that combines different models and techniques to solve a real-world problem. You’ll learn to incorporate data preprocessing, model selection, and evaluation in a structured workflow.

  • Objective: Explain how a single AI/ML project can use different models and techniques to address a complex problem.
  • Visual: Mind Map of Project Workflow, highlighting each component like data preprocessing, model selection, and evaluation.

2. Concept Explanation

This section introduces fundamental ML concepts such as supervised learning, feature selection, and model evaluation, providing a solid foundation for developing multi-feature AI projects.

  • Overview: Introduces foundational ML principles essential for selecting and evaluating models based on project goals.
  • Visual: Annotated Model Selection Flowchart, showing the steps for choosing between models (e.g., linear regression, image classifier) based on data.

3. Hands-On Example: Predictive Analytics with ChatGPT

In this hands-on guide, you’ll build a predictive analytics model using ChatGPT for data generation and prompts for model development. This example covers the process from data preprocessing to final predictions.

  • Objective: Step-by-step guide to create a model for predictive analytics using generated data.
  • Visual: Data Preprocessing Flowchart, which illustrates cleaning, processing, and preparing data for predictive analysis.

4. Hands-On Example: Image Recognition

This example focuses on building a basic image classification model. You’ll use ChatGPT prompts to fine-tune the model and improve accuracy.

  • Objective: Guide to developing an image classification model with steps for loading data, training, and evaluating.
  • Visual: Image Classification Process Diagram, showing each stage from data loading to model evaluation.

5. Hands-On Example: Natural Language Processing (NLP)

This example covers the basics of creating a text summarizer or sentiment analyzer. You’ll learn common NLP tasks such as tokenization, feature extraction, and model building.

  • Objective: Guide to building an NLP model, covering text preprocessing and common NLP model tasks.
  • Visual: NLP Pipeline Flowchart, outlining steps for text preprocessing, tokenization, and model building.

6. Practice Exercises

Explore practical use cases for predictive, image, and NLP models across different industries like e-commerce, healthcare, and finance. These exercises provide inspiration for integrating multiple AI features into your project.

  • Inspiration: Examples of applications for predictive, image, and NLP models in real-world settings.
  • Visual: Application Ideas Grid, showcasing project ideas across various sectors.

7. Summary and Key Takeaways

This chapter provided a comprehensive approach to building a multi-feature AI/ML project. From data preprocessing to model evaluation, each step was covered to help you understand how to integrate multiple techniques into a cohesive project.

  • Key Takeaway: The importance of combining different ML models to solve complex problems and enhance project versatility.
  • Visual: Project Checklist, ensuring each development stage, from data preparation to evaluation, is completed effectively.

Chapter 5: Examples of Prompts and Results

Introduction

This chapter provides an example bank of prompt and response pairs, demonstrating the impact of refined prompts across different applications.

1. Portfolio Website Content Prompts

Example: Image Classification Project Description

Basic Prompt: “Write a brief project description for an image classification model.”

Response: “Built an image classification model with 98% accuracy for identifying product categories in an e-commerce dataset.”

Refined Prompt: “Write a 50-word project summary with an emphasis on business impact and accuracy.”

Response: “Developed an image classification model with 98% accuracy, automating the categorization process for an e-commerce company, which increased efficiency and reduced manual effort.”

2. AI/ML Project Documentation Prompts

Example: Regression Model Summary

Basic Prompt: “Summarize my regression model’s performance on housing price predictions.”

Response: “The model predicts house prices with a high accuracy based on factors like location and size.”

Refined Prompt: “Describe my regression model’s accuracy and key predictors, emphasizing its value for real estate decisions.”

Response: “Our regression model accurately forecasts housing prices, considering variables such as size, location, and number of bedrooms, helping real estate investors make informed decisions.”

3. Creative Content Generation

Example: Blog Introduction on AI in Business

Basic Prompt: “Write an engaging introduction to a blog on AI in business.”

Response: “Artificial intelligence is transforming the way businesses operate, from enhancing customer service to automating data analysis. As companies adopt AI, they unlock new levels of efficiency and competitive advantage.”

Refined Prompt: “Write a dynamic and engaging introductory paragraph for a blog on the importance of AI in transforming business operations.”

Response: “Artificial intelligence is reshaping how businesses operate, from customer service to data analysis. As more companies adopt AI, they’re seeing enhanced efficiency, better decision-making, and a competitive edge.”

4. Comparison Table for Refined Prompt Results

This table highlights how refining prompts can improve the specificity and tone of responses:

Basic Prompt Refined Prompt Basic Response Refined Response
“Write a short description for an image classification project.” “Write a 50-word summary emphasizing business impact and accuracy.” “Built an image classification model with 98% accuracy.” “Developed a model with 98% accuracy, automating image categorization for an e-commerce company, boosting efficiency.”
“Summarize my regression model’s performance.” “Describe accuracy and key predictors in layman’s terms.” “The model predicts house prices accurately.” “Predicts house prices using size, location, and rooms, aiding real estate investment.”
“Write a blog intro about AI in business.” “Write an engaging blog intro about AI’s role in business transformation.” “AI is transforming business.” “AI reshapes businesses, driving efficiency and a competitive edge.”

5. Tips and Tricks for Prompt Refinement

6. Summary and Key Takeaways

Chapter 6: Writing a Book with AI

Learn how to plan, outline, and create a book using AI tools.

1. Planning and Outlining the Book

Learn how to brainstorm, plan, and organize your book’s structure with the help of ChatGPT. Use prompts to develop chapter outlines, create character descriptions, and establish plot points, ensuring a cohesive narrative.

  • Prompt Example: “Generate an outline for a book on machine learning fundamentals.”
  • Response: ChatGPT provides a list of chapters covering foundational topics such as supervised learning, unsupervised learning, model evaluation, etc.
  • Refinement: “Organize the chapters for beginners, ensuring each builds on the last.”
  • Response: A revised outline that progresses logically from basic to complex topics, making it easier for beginners to follow.

Activity:

Use similar prompts to create an outline for your book idea. Experiment with ChatGPT to structure chapters and ensure a logical flow that suits your intended audience.

2. Writing and Generating Chapter Content

Once you have an outline, you can use ChatGPT to generate content for each chapter. AI can help create introductions, main content, examples, and summaries that match the tone and style you need.

  • Prompt Example: “Write an introductory paragraph for a chapter on neural networks.”
  • Response: A clear, beginner-friendly paragraph introducing neural networks, suitable for non-technical readers.
  • Expanding Ideas: “Explain supervised learning with three real-world use cases.”
  • Response: ChatGPT lists use cases such as predicting housing prices, diagnosing diseases, and recommending personalized content.

Exercise:

Generate different sections for a chapter in your book using prompts. Customize your prompts to generate content for specific audiences, such as beginners or advanced readers.

3. Editing and Refining Text

After generating content, refine it using AI prompts to improve clarity, engagement, and tone. ChatGPT can help rephrase, summarize, and adjust the content to suit different audiences.

  • Editing Prompt: “Rewrite this paragraph to make it more engaging for readers.”
  • Response: A revised, more captivating version of the paragraph.
  • Summarization Prompt: “Summarize this section in 50 words or fewer.”
  • Response: A concise summary that highlights the key points of the section.

Activity:

Practice refining a draft by prompting ChatGPT to make adjustments. Request specific changes, such as clarifying explanations, adding examples, or adjusting tone.

4. Book Planning Templates and Prompts

These prompts and templates can help you structure your book, develop characters, create plot points, and ensure narrative coherence. Use them to guide your brainstorming and planning phases.

  • Template Prompt: “Outline the chapters for a book on AI for beginners, with each chapter focusing on a different aspect of AI.”
  • Character Development Prompt: “Describe a character with a background in AI, focusing on their personality, skills, and motivations.”
  • Plot Development Prompt: “Create a storyline for a sci-fi novel where AI changes society, highlighting key conflicts and resolutions.”

5. Content Creation Modules for Different Writing Styles

Adjust your book’s tone and style using targeted prompts. Whether you're writing a technical manual or a narrative, ChatGPT can adapt the content to fit.

  • Technical Writing Prompt: “Explain neural networks in a technical manner suitable for advanced readers.”
  • Response: An in-depth explanation of neural networks, with technical jargon and detailed analysis.
  • Non-Technical Writing Prompt: “Explain neural networks in simple terms, suitable for non-technical readers.”
  • Response: An accessible introduction to neural networks, using relatable analogies and simple language.

6. Advanced Editing and Refinement Techniques

Use ChatGPT to further polish your writing, with prompts that enhance readability and engagement. Experiment with rephrasing and summarizing prompts to make your content more compelling.

  • Rephrasing Prompt: “Rewrite this paragraph to make it more engaging and easier to read.”
  • Response: A rephrased version that is more accessible and engaging for readers.
  • Clarity Prompt: “Summarize this paragraph for a general audience in 30 words.”
  • Response: A clear, concise summary for non-technical readers.

7. Practice Exercises

  • Exercise 1: Outline a book on a topic of your choice, using prompts to generate chapter titles and descriptions.
  • Exercise 2: Write an introductory paragraph for a chapter using ChatGPT, then refine it to match a specific tone.

8. Summary and Key Takeaways

  • Generative AI can assist at each stage of book writing, from brainstorming and structuring to content generation and editing.
  • Using prompts strategically can help create engaging, well-structured content for a variety of audiences.
  • AI-driven editing prompts allow for fine-tuning of tone, style, and clarity, making AI a powerful assistant for authors.