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38.9 MB
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June 23, 2025, 11:35 a.m.
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(Last updated: June 23, 2025, 11:35 a.m.)
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38.9 MB
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2025-06-23
| Uploaded by andryold1 | Size 38.9 MB | Health [ 42 /25 ] | Added 2025-06-23 |
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SOURCE: Haba D. Python Simplified with Generative AI. Hands-on Python development...2025
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Textbook in PDF format This book bridges the gap between traditional education and the practical challenges students encounter today. Instead of relying on conventional programming guides, it combines hands-on learning with modern Generative AI tools like GPT-4o and Copilot. Written by college students alongside an experienced AI expert, it focuses on meeting the needs of a generation that thrives on creativity, quick access to information, and learning through practical experience. This book takes a fresh approach to learning by prioritizing exploration and creativity, much like the way Gen Z engages with games, apps, and hands-on activities. Instead of starting with technical details like algorithms and syntax, it introduces coding through interactive, practical projects in Python Jupyter Notebooks. These projects are relatable and grounded in everyday experiences, making the process intuitive and enjoyable. It is designed specifically for college students who find conventional programming textbooks intimidating. It offers a flexible and personalized learning method, demonstrating how GenAI tools can support your studies. You'll explore Python fundamentals through practical projects while building confidence in your programming skills. The hands-on approach fosters creativity and curiosity, making applying what you have learned to other areas like science, history, or communication easier. By the end of this book, you will acquire practical skills beyond just understanding Python code. You will learn how to confidently write and debug Python programs using Jupyter Notebooks, working through projects that reflect real-world applications. Throughout this journey, you will also gain a deeper understanding of how to integrate Generative AI tools, such as GPT-4 and Copilot, into your workflow. These tools will serve as collaborators, enhancing your learning and problem-solving abilities. You will enhance your creative thinking abilities and tackle coding challenges with curiosity and resourcefulness. In addition to coding, the book provides you with transferable skills applicable to various fields. These skills include breaking down complex problems, experimenting with solutions, and adapting tools to meet your needs. Whether you apply these skills in science, history, communication, or other areas, you will gain a strong foundation for learning in an AI world. Chapter 1: Introduction to GenAI - This chapter is your introduction to Generative AI, focusing on getting started with ChatGPT-4. You will learn what makes GenAI unique, how it works, and the practical ways it can assist you in solving problems, creating content, and exploring new ideas. The chapter provides a step-by-step guide on setting up and accessing GPT-4, ensuring you can start using it immediately. You will also gain insights into prompt engineering—crafting inputs that guide the AI to deliver precise and valuable results. By the end, you will understand how to navigate and use GPT-4 effectively, making it a valuable part of your learning and work process. Chapter 2: Jupyter Notebook - In this chapter, you will learn about the practical uses of Python Jupyter Notebooks, specifically in the Google Colab environment. The focus will be on combining live code with text, visuals, and interactive widgets, creating a versatile space for data analysis and experimentation tasks. Instead of diving into Python programming immediately, this chapter prioritizes understanding the features of Jupyter Notebooks. You will also explore tools like GPT-4o to help generate and analyze code. Through practical examples, you will develop the skills to explore the tool's capabilities and tailor it to your needs, laying a solid groundwork for more advanced learning in subsequent sections. Chapter 3: Dissect The Calculator App - This chapter looks at how Generative AI, such as ChatGPT-4o, can enhance your learning of Python programming through a practical project in Jupyter Notebooks. Using a Python-based calculator app as an example, it shows how to break down and understand the code with the support of GenAI's analytical tools. You will follow a clear, step-by-step guide for building the app, using AI to clarify concepts, explain the logic behind the code, and offer suggestions for improvements. Whether you are a beginner or just seeking a new way to learn, this chapter provides a practical approach that combines GenAI assistance with programming, helping you better understand complex concepts and build your confidence in coding. Chapter 4: Sorting on My Mind - This chapter offers a detailed look at sorting algorithms using Python Jupyter Notebooks and GPT-4o for an interactive learning experience. Sorting is an essential topic in computer science, and it is crucial to understand how different algorithms work for programming and data processing. You will study various algorithms, from bubble sort to quick sort, and implement them in Python to understand their logic and uses. With the help of GPT-4o, you will receive explanations, answers to questions, and code suggestions in real time, providing a personalized learning experience. This hands-on method is designed for learners of all levels to enhance their understanding of sorting algorithms and improve their Python programming skills in an engaging and supportive setting. Chapter 5: Pandas, the Data Tamer - This chapter covers the Pandas library in Python, which is essential for data manipulation and analysis. It also discusses using Generative AI tools like GPT-4o to write Python Pandas code. This chapter suits learners of all levels and focuses on practical applications. You will learn about Pandas’ main features, including working with dataframes and series, cleaning and visualizing data, and applying advanced data manipulation techniques. With the help of Generative AI, the chapter provides straightforward explanations, code examples, and answers your questions to help you understand these concepts better. By engaging in hands-on practice using Jupyter Notebooks, you will develop the skills to work with real-world data and improve your data analysis abilities. Chapter 6: Decipher CNN App - This chapter covers the steps to create an image classification app using Convolutional Neural Networks ( CNNs ) with Fast.ai. You will gain hands-on experience in organizing projects, preparing image data, and training CNNs while receiving real-time assistance to help clarify concepts and answer questions related to coding. By the end of the chapter, you will understand how CNNs detect image patterns, apply these methods to real-world situations, and use AI tools to support your learning. This practical approach involves working with Python, Fast.ai, and AI assistance to make image classification more accessible. Chapter 7: Gradio and Hugging Face Deployment - This chapter introduces the practical integration of Hugging Face, Gradio, and ChatGPT-4 within Python Jupyter Notebooks, focusing on building and deploying interactive AI applications. You will learn to access and implement advanced Hugging Face models, such as those for natural language processing, and connect them to user-friendly Gradio interfaces for web-based interaction. Along the way, ChatGPT-4o serves as a coding assistant, helping to explain concepts, debug code, and guide you through challenges. By the end of this chapter, you will have the skills to set up a working AI web application, gaining hands-on experience in deploying AI models while improving your understanding of the technology and its real-world applications. Chapter 8: Fairness and Bias - Chapter 8 explores the critical issues of AI fairness and ethics, using ChatGPT-4o as both a learning tool and a case study. It delves into how biases can arise in AI and GenAI systems, from biased training data to technical decisions, and examines their real-world impacts, such as algorithmic discrimination. Readers will gain practical insights into recognizing and questioning potential biases in AI outputs, learn about current efforts to create fairer AI systems and understand their role as users in advocating for ethical AI practices. By the end of the chapter, you will be equipped to critically evaluate AI and GenAI technologies, make informed decisions in using them, and contribute to a future where AI aligns more closely with human values. Chapter 9: Your Turn to Be a Code Walker - The last chapter focuses on helping readers determine if a career in programming and computer science is a good fit for their skills, interests, and goals. It looks at the changing role of GPT-4o in programming. It provides a straightforward overview of the field, including the various job opportunities, the importance of problem-solving and teamwork, and the impact of AI-assisted coding. Readers will learn about the necessary skills and mindset for programming, how to use GenAI as a helpful tool, and the overall job landscape in the technology sector. By the end of the chapter, readers will better understand the challenges and benefits associated with pursuing a career in programming, allowing them to make informed choices about their future
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