This program offers a detailed exploration of AI-powered software development, guiding participants through the latest advancements and practical applications of intelligent coding tools. Tailored for developers, software engineers, and technical leads, it provides the skills to effectively integrate AI coding assistants such as GitHub Copilot, Tabnine, and Amazon Q into real-world projects.


您将学到什么
Define how AI coding tools assist in software development.
Construct effective prompts for accurate AI code suggestions.
Apply GitHub Copilot, Tabnine, and Amazon Q to generate, debug, and document code.
Collaborate with AI tools in both solo and team-based coding tasks.
您将获得的技能
- Maintainability
- AI Personalization
- Prompt Engineering
- Test Automation
- GitHub
- Software Technical Review
- Integrated Development Environments
- CI/CD
- Software Architecture
- Generative AI Agents
- Secure Coding
- Generative AI
- Code Review
- Artificial Intelligence and Machine Learning (AI/ML)
- Software Development Tools
- Software Documentation
- Amazon Web Services
- Software Development
- DevOps
- Software Engineering
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书

该课程共有4个模块
This module introduces learners to GitHub Copilot, focusing on AI-powered code suggestions, debugging, documentation, and reviews. Learners gain hands-on experience in enhancing individual productivity, improving code quality, and streamlining collaboration with features like Copilot Chat, AI pair programming, and CI/CD integration.
涵盖的内容
21个视频7篇阅读材料5个作业4个讨论话题2个插件
This module explores Tabnine AI as a personalized coding assistant for smarter, faster, and more secure software development. Learners gain hands-on experience with context-aware code completions, inline actions, and AI-powered chat to boost productivity, improve testing, streamline documentation, and enhance team workflows.
涵盖的内容
16个视频4篇阅读材料5个作业4个讨论话题1个插件
This module focuses on Amazon Q Developer, equipping learners with skills to generate, transform, and review code while integrating seamlessly with AWS workflows. Through hands-on practice, learners explore inline suggestions, testing, cross-platform debugging, and advanced CLI usage—gaining the expertise to streamline development, enhance collaboration, and ensure secure, scalable software with Amazon Q.
涵盖的内容
13个视频3篇阅读材料4个作业3个讨论话题1个插件
This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz.
涵盖的内容
1个视频1篇阅读材料2个作业1个讨论话题
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
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常见问题
Yes! The course includes interactive demos and guided exercises using GitHub Copilot, Tabnine, and Amazon Q. You'll learn by doing—writing, reviewing, debugging, and deploying code with AI assistance.
You’ll learn how to use AI tools to generate code, fix bugs, document projects, collaborate in teams, and integrate AI into development workflows like CI/CD and DevOps.
Basic familiarity with coding is helpful, but not mandatory. The course is beginner-friendly and includes clear explanations, sample prompts, and walkthroughs to get you started.
更多问题
提供助学金,
¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。