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
Software development is being transformed by GenAI tools, such as 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 practical 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.
If 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.
(N.B. Please use the Read Sample option to see further chapters)
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Hila Paz Herszfang, with seven years of building machine learning (ML) services and leading teams, holds a master's degree in information management systems and is completing a second master's in data science, both from Harvard Extension School. She developed a Python for MLOps Udemy course and runs a math and tech TikTok channel boasting 15K followers and 300K+ likes.
Peter V. Henstock is an AI expert with 25+ years of experience at Pfizer, Incyte, and MIT LL. He teaches graduate software engineering and AI/ML courses at Harvard Extension School. He holds a PhD in AI from Purdue and seven Master's degrees. Recognized as a top AI leader by DKA, Peter guides professionals in AI/ML, software, visualization, and statistics.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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