Supercharged Coding with GenAI: From vibe coding to best practices using GitHub Copilot, ChatGPT, and OpenAI (Record no. 51962)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02369 a2200205 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251126210035.0 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781836645290 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.1 HER |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Herszfang, Hila Paz |
| 245 ## - TITLE STATEMENT | |
| Title | Supercharged Coding with GenAI: From vibe coding to best practices using GitHub Copilot, ChatGPT, and OpenAI |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc | Packt Publishing Ltd. |
| Date of publication, distribution, etc | 2025 |
| Place of publication, distribution, etc | UK |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 425 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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.<br/>What you will learn<br/>Work with GitHub Copilot in PyCharm, VS Code, and Jupyter Notebook<br/>Apply advanced prompting methods with ChatGPT and OpenAI API<br/>Gain insight into GenAI fundamentals to achieve better outcomes<br/>Adopt our structured framework to produce high-quality code<br/>Find out how to select the optimal GenAI tool for solving your specific tasks<br/>Elevate your use of GenAI tools from debugging to delivery<br/>Join the next generation of supercharged software engineers |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Coding With AI |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | ChatGPT |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | OpenAI |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Copilot, |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Henstock, Peter V. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Book |
| Source of classification or shelving scheme | Dewey Decimal Classification |
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