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Full Description
Unlock the power of generative AI in Python development and learn how you can enhance your coding speed, quality, and efficiency with real-world examples and hands-on strategies
Key Features
Discover how GitHub Copilot, ChatGPT, and the OpenAI API can boost your coding productivity
Push beyond the basics to apply advanced techniques across the software development lifecycle
Master best practices and advanced techniques to achieve quality code for even complex tasks
Purchase of the print or Kindle book includes a free PDF eBook
Book DescriptionSoftware development is being transformed by GenAI tools like ChatGPT, OpenAI API, and GitHub Copilot, redefining how developers work. This book will help you become a power user of GenAI for Python code generation, enabling you to write better software faster. Written by an ML advisor with a thriving tech social media presence and a top AI leader who brings Harvard-level instruction to the table, this book combines practical industry insights with academic expertise.
With this book, you'll gain a deep understanding of large language models (LLMs) and develop a systematic approach to solving complex tasks with AI. Through real-world examples and hands-on exercises, you'll master best practices for leveraging GenAI, including prompt engineering techniques like few-shot learning and Chain-of-Thought (CoT).
Going beyond simple code generation, this book teaches you how to automate debugging, refactoring, performance optimization, testing, and monitoring. By applying reusable prompt frameworks and AI-driven workflows, you'll streamline your software development lifecycle (SDLC) and produce high-quality, well-structured code.
By the end of this book, you'll know how to select the right AI tool for each task, boost efficiency, and anticipate your next coding moves—helping you stay ahead in the AI-powered development era.What you will learn
Work with GitHub Copilot in PyCharm, VS Code, and Jupyter Notebook
Apply advanced prompting methods with ChatGPT and the OpenAI API
Gain insight into GenAI fundamentals to achieve better outcomes
Adopt our structured framework to produce high-quality code
Find out how to select the optimal GenAI tool for solving your specific tasks
Elevate your use of GenAI tools from debugging to delivery
Join the next generation of supercharged software engineers
Who this book is forIf you are a Python developer curious about GenAI and are looking to elevate your software engineering productivity, Supercharged Coding with GenAI will transform your approach to software. Covering various structured examples of varying problem complexities that showcase the use of advanced prompting techniques, this book is suitable for early intermediate through advanced developers. To get the most out of this book, you should have at least one year of hands-on Python development experience and be somewhat familiar with the SDLC.
Contents
Table of Contents
From Boilerplates Automation to Software Development Lifecycle Smoothing: What GenAI Can Do for Your Code
Quickstart Guide: GitHub Copilot with PyCharm , VSCode and Jupyter
Quickstart Guide: Supercharged Coding with GenA
Beyond the UI: Quickstart Guide to the OpenAI API
Quickstart Guide: Prompt Engineering for Coding
Behind the Scenes: How ChatGPT, Github Copilot and other LLMs Work
Great Assistant, Risky Leader: How AI Hallucinations, Temperature and Errors Can Derail Your Career
Advanced Prompting Techniques: CoT Prompting, Reinforcement Prompting, Iterative Prompting, Few-Shots Prompting
Speed-Reading GenAI Code: Techniques for Quick Comprehension
Extreme Accountability: Owning Your GenAI Code Through Input and Output Evaluation Metrics
Refactoring Code with Prompt Engineering: Asking the Right Questions
Single Responsibility and Other Coding Standards through Fine-Tuning with OpenAI API
Optimizing Performance: Scaling Applications with GenAI for Memory and CPU Efficiency
Logging, Monitoring and Error Handling through Prompt Engineering
Quick Debugging and Cleanup: Managing Junk Files with GenAI
Writing and Maintaining Unit Tests Suites with ChatGPT
Documenting Your Code with GenAI
Generating Non-Project Files with GenAI: From requirements.txt to Docker Files and Beyond
Architecture, Design and the Future
