GitHub Copilot Certification Study Guide

• Autore: Taulli Tom
• Pubblicazione: Newark : , : John Wiley & Sons, Incorporated, , 2025; ©2025
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (242 pages)
• Disciplina: 006.3/5
• Soggetto topico: Computer software - Development - Certification; Computer software - Development - Examinations; Artificial intelligence - Computer programs - Certification; Artificial intelligence - Computer programs - Examinations
• Note generali: Electronic book.
• Nota di contenuto: Cover -- Title Page -- Copyright -- Contents -- Acknowledgments -- About the Author -- About the Technical Editor -- Introduction -- Assessment Test -- Answers to Assessment Test -- Chapter 1: The Fundamentals of AI and Its Responsible Use -- AI Coding and GitHub Copilot -- Programming Languages and Abstraction -- The Basics of AI -- Machine Learning (ML) -- Deep Learning (DL -- Generative AI (GenAI) -- The Risks and Drawbacks of GenAI -- Hallucinations -- Bias -- Security Threats -- Black Box Concerns -- Low-Quality Code -- Limited Context Windows -- Recency Problem -- High Costs -- Responsible AI -- Fairness -- Reliability and Safety -- Privacy and Security -- Inclusiveness -- Transparency -- Accountability -- Multimodel AI Coding -- How AI Makes Software Development Different -- Types of AI Coding Tools -- Amazon Q Developer -- Gemini Code Assist -- Cursor -- V0 -- Replit -- Summary -- Exam Essentials -- Review Questions -- Notes -- Chapter 2: Introduction to GitHub Copilot -- Benefits of GitHub Copilot -- Productivity -- Code Quality -- Pair Programming -- Full-Stack Development -- Learning New Languages -- Attracting and Retaining Talent -- Microsoft and GitHub -- Case Studies -- AMD -- SAP -- Drawbacks of GitHub Copilot -- Versions of GitHub Copilot -- GitHub Accounts -- Free Plan -- Team Plan -- Enterprise Plan -- GitHub Copilot Setup -- Features of GitHub Copilot -- Chat -- Other Chat Features -- Slash Commands -- @ References -- Extensions -- Chat Variables -- Inline Chat -- Code Completion -- Edits -- Integrations -- GitHub.com -- GitHub Mobile -- GitHub Copilot for Azure -- GitHub Copilot in the CLI -- Summary -- Exam Essentials -- Review Questions -- Notes -- Chapter 3: Differences in GitHub Copilot Versions -- GitHub Copilot Individual -- Pull Request Summaries -- AI-Native Experiences -- Management and Policies -- Customization. ; GitHub Copilot Business -- User Management -- Data Exclusion -- IP Indemnity -- Audit Logs -- GitHub Copilot Enterprise -- Knowledge Bases -- Creating and Using a Knowledge Base -- Custom Models -- The Key Differences -- Summary -- Exam Essentials -- Review Questions -- Notes -- Chapter 4: The Role of Data -- The World of Data -- Not Enough Data? -- Data Flows in LLM Development -- Problem Framing -- Data Collection -- Data Preprocessing -- Training the Model -- Model Deployment and Monitoring -- Data Security -- Data in GitHub Copilot Individual -- Telemetry Data -- Contextual Information -- User Feedback -- Data Flow for GitHub Copilot -- Prompt Crafting -- Model Processing -- Post-Processing -- Safety -- Limitations of GitHub Copilot When Using Data -- Reasoning and Context vs. Calculations -- Summary -- Exam Essentials -- Review Questions -- Notes -- Chapter 5: Prompt Crafting and Engineering -- Different Mindset -- Issues with Prompt Engineering -- Fundamentals of Prompt Engineering -- Prompt Structure -- Context -- Instructions for the LLM -- Input of Content -- Format -- Best Practices -- Be Clear -- Leading Questions -- Use Analogies or Comparisons -- Ask for Alternatives -- Zero- and Few-Shot Learning -- Chain-of-Thought (CoT) Prompting -- Mitigating Hallucinations -- Security and Privacy -- Multimodal Systems -- Language Support -- The Future of Prompt Engineering -- Summary -- Exam Essentials -- Review Questions -- Note -- Chapter 6: Developer Use Cases for GitHub Copilot -- Learning -- Learning a Language or Framework -- Comparing Languages -- Study Guides -- Code Challenges -- Documentation -- Comments -- User Guides -- Common Language Capabilities -- Loops, Conditionals, and Variables -- Data Structures -- Functions -- Code Translation -- Code Refactoring -- Extract Method -- Decomposing Conditionals -- Deciphering Ninja Code. ; Identifying Dead Code -- Data Creation -- Database Schemas and SQL -- Data Conversion -- Debugging -- Regular Expressions (Regex -- The Software Development Life Cycle (SDLC) -- Requirements Analysis -- Deployment -- REST API -- Summary -- Exam Essentials -- Review Questions -- Notes -- Chapter 7: Testing and Privacy Considerations -- Background on Testing -- Approaches to Testing -- Unit Testing -- Example of a Unit Test -- Best Practices for Unit Testing -- Integration Testing -- Testing Using GitHub Copilot -- Using /tests -- Custom Prompts -- Integration Tests -- Security Testing -- Privacy Fundamentals -- Privacy for Versions of GitHub Copilot -- Organization-Wide Policy Management Exclusion of Files -- Audit Logs -- Content Exclusions -- Policy Management -- Block Suggestions Matching Public Code -- Troubleshooting -- GitHub Advanced Security -- Summary -- Exam Essentials -- Review Questions -- Notes -- Appendix: Answers to Review Questions -- Index -- EULA.
• Sommario/riassunto: The fastest, most effective way to prepare for the GitHub Copilot certification exam and hone your skills with the popular AI-powered programming tool In the GitHub Copilot Certification Study Guide, tech entrepreneur and Pluralsight trainer, Tom Taulli, delivers a concise and accurate walkthrough of the AI-powered programming tool.
• Titolo autorizzato: GitHub Copilot Certification Study Guide
• ISBN: 1-394-34999-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911113364703321
• Lo trovi qui: Univ. Federico II
• Serie: Sybex Study Guide Series