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.
You’ll begin by mastering GitHub Copilot, exploring how to supercharge coding with intelligent code suggestions, debugging support, documentation, and collaborative workflows. From personalized completions to advanced integrations in CI/CD pipelines, you’ll gain hands-on expertise in applying Copilot effectively across individual and team development.
Next, you’ll dive into Tabnine AI, unlocking context-aware completions, inline actions, and AI-powered chat to boost productivity. You’ll learn how to review, refactor, and document code with AI, while also addressing security and ethical considerations in modern development. Tabnine’s integrations and maintenance capabilities will help you streamline large-scale projects with confidence.
The program concludes with Amazon Q for Developers, Amazon’s powerful AI assistant for coding and cloud-based development. You’ll explore setup, configuration, and practical usage of commands like /transform and /dev to generate, refactor, and test code. By comparing Amazon Q with Copilot and Tabnine, you’ll understand their strengths and trade-offs, empowering you to select the right AI tool for diverse workflows.
By the end of this program, you will be able to:
- Accelerate development with GitHub Copilot for intelligent suggestions, debugging, reviews, and DevOps automation.
- Boost productivity with Tabnine AI for context-aware completions, code review, documentation, and secure coding practices.
- Harness Amazon Q Developer for inline suggestions, code transformation, testing, and AWS integration.
- Collaborate effectively in multi-developer projects using AI to enhance pull requests, code reviews, and pair programming.
- Apply AI responsibly to build secure, scalable, and maintainable software across the entire development lifecycle.
This program is ideal for software engineers, DevOps professionals, and technical leads aiming to integrate AI seamlessly into their coding workflows. A foundational understanding of programming concepts, version control, and software development best practices is recommended.
Join us to unlock the power of AI in software engineering and transform the way you code, collaborate, and innovate.
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
显示有关单元内容的信息
21个视频•总计113分钟
Specialization Introduction•7分钟
Course Introduction•6分钟
Introduction to GitHub Copilot•5分钟
Basic Code Suggestion & Completion in Copilot•5分钟
Demonstration: Blog Platform for Software Developers•7分钟
Supercharging Your Coding with Copilot Chat•7分钟
Demonstration: Expense Tracker Application•4分钟
Semantic Indexing and Finding Matching Code•3分钟
Copilot for Debugging and Error Resolution•7分钟
Enhancing Code with Refactoring and Feature Suggestions•7分钟
Copilot for Documenting & Testing Your Code•7分钟
Copilot for Code Review: Streamlining Code Reviews•5分钟
Copilot with Team Coding Standards and Workflows•3分钟
Best Practices for Collaborative Coding with Copilot•4分钟
Copilot for Pull Requests: Enhancing Collaboration•5分钟
Managing Copilot Usage in Multi-Developer Projects•4分钟
Automating Development with GitHub Copilot Coding Agent•4分钟
Copilot in CI/CD Pipelines•4分钟
Optimizing Copilot’s Impact on Developer Workflow•7分钟
Prompt Engineering with GitHub Copilot•7分钟
Demonstration: Copilot Agent Mode in Action•4分钟
7篇阅读材料•总计105分钟
Course Overview•15分钟
The Rise of AI in Software Development•15分钟
Best Practices for AI-Assisted Code Suggestions•15分钟
Debugging in the Age of AI: Human + Machine Synergy•15分钟
AI Pair Programming: A New Era of Collaboration•15分钟
From Suggestions to CI/CD: Bridging AI Coding Tools with DevOps•15分钟
Module Summary: GitHub Copilot for Software Developers•15分钟
5个作业•总计54分钟
Knowledge Check: GitHub Copilot for Software Developers•30分钟
Practice Quiz: Getting Started with GitHub Copilot•6分钟
Practice Quiz: Advanced Copilot Techniques & Code Quality•6分钟
Practice Quiz: Copilot in Team Environments and Collaborative Development•6分钟
Practice Quiz: Advanced Copilot Customization & Management•6分钟
4个讨论话题•总计20分钟
Introduce Yourself•5分钟
Prompt: AI vs Human in Debugging•5分钟
Copilot in Team Collaboration•5分钟
Writing Better Prompts for Better Code•5分钟
Tabnine AI for Software Developers
第 2 单元•小时 后完成
单元详情
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
显示有关单元内容的信息
16个视频•总计92分钟
Tabnine and its Role in Code Development
•7分钟
Demonstration: Step-by-Step Guide on Installing and Configuring Tabnine•7分钟
Deep Dive into the Components of Tabnine•6分钟
Personalized AI Coding with Tabnine•6分钟
Demonstration: Context-Aware Coding with Tabnine•5分钟
Maximizing Productivity with Tabnine Code Completions•4分钟
Demonstration: Getting the Most from Tabnine Code Completions•5分钟
AI-Powered Chat for Smarter Development•4分钟
Demonstration: Supercharging Your Workflow with Inline Actions•6分钟
Planning and Building with Tabnine•6分钟
Smarter Testing with Tabnine•7分钟
Review and Fix Code with Tabnine•6分钟
Document, Explain, and Refactor with Tabnine•6分钟
Tabnine AI Agents for Atlassian Jira•7分钟
Empowering Development Teams with Tabnine•6分钟
The Future of Tabnine - Roadmap and Beyond•5分钟
4篇阅读材料•总计60分钟
Code Security in the Era of AI Assistance•15分钟
The Ethics of AI Code Generation•15分钟
The Future of AI-Driven Documentation•15分钟
Module Summary: Tabnine AI for Software Developers•15分钟
5个作业•总计54分钟
Knowledge Check: Tabnine AI for Software Developers•30分钟
Practice Quiz: Introduction to Tabnine AI and Setup•6分钟
Practice Quiz: Tabnine Integration and Practical Coding•6分钟
Practice Quiz: Leveraging Tabnine for Efficient Development•6分钟
Practice Quiz: Streamlining Software Maintenance with Tabnine•6分钟
4个讨论话题•总计20分钟
Understanding Tabnine Under the Hood•5分钟
Evaluating Inline Actions in Practice•5分钟
Rethinking Documentation with AI•5分钟
Scaling AI Support Across Teams•5分钟
Mastering Amazon Q for Developers
第 3 单元•小时 后完成
单元详情
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
显示有关单元内容的信息
13个视频•总计67分钟
What is Amazon Q Developer?•5分钟
Chatting with Amazon Q: Basic Interaction and AWS Support•5分钟
Amazon Q Essentials: Plugins, Code Conversion and Detector Library•5分钟
Demonstration: Step-by-Step S3 Bucket Setup with Amazon Q Assistance•5分钟
Generating Inline Code Suggestions with Amazon Q•4分钟
Transforming Code with Amazon Q’s /transform Command•5分钟
Developing New Features Using the /dev command•4分钟
Code Quality with Amazon Q: Unit Tests, Reviews and Documentation•5分钟
Demonstartion: Seamless Data Exploration in Redshift Using Amazon Q•6分钟
Getting Started and Troubleshooting with Amazon Q CLI•6分钟
Cross-Platform Development and Debugging with Amazon Q•4分钟
Code Transformation and Secure Development with Amazon Q•6分钟
Demonstartion: Serverless Event Notifications with S3, Lambda, and SNS•7分钟
3篇阅读材料•总计45分钟
AI Assistants in Large Teams: Scaling Collaboration•15分钟
Comparing GitHub Copilot, Tabnine, and Amazon Q: Strengths and Tradeoffs•15分钟
Module Summary: Mastering Amazon Q for Developers•15分钟
4个作业•总计48分钟
Knowledge Check: Mastering Amazon Q for Developers•30分钟
Practice Quiz: Introduction to Amazon Q Developer & Core Functionality•6分钟
Practice Quiz: Amazon Q for Coding: Streamlining Development•6分钟
Practice Quiz: Advanced Usage & Integration of Amazon Q•6分钟
3个讨论话题•总计15分钟
Effectiveness of Conversational AI in Development•5分钟
Code Transformation Capabilities•5分钟
Versatility of Amazon Q in Diverse Environments•5分钟
Course Wrap-Up and Assessment
第 4 单元•小时 后完成
单元详情
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
显示有关单元内容的信息
1个视频•总计4分钟
Course Summary: Generative AI Coding Assistants for Developers•4分钟
1篇阅读材料•总计30分钟
Practice Project: BugTracker Pro - Real-World Development Challenge•30分钟
2个作业•总计90分钟
End Course Knowledge Check: Generative AI Coding Assistants for Developers•60分钟
Designing an AI-Powered Software Development Workflow with Copilot, Tabnine, and Amazon Q•30分钟
Edureka is an online education platform focused on delivering high-quality learning to working professionals. We have the
highest course completion rate in the industry and we strive to create an online ecosystem for our global learners to equip
themselves with industry-relevant skills in today’s cutting edge technologies.
Will I get hands-on practice with AI developer tools?
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.
What skills will I gain from this course?
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.
Do I need to know programming before taking this course?
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.
How long will it take to complete the course?
You can complete the course in about 4–5 weeks, spending 4 to 5 hours per week. The pace is flexible, so you can revisit lessons, demos, and quizzes anytime.
What AI tools will I use in this course?
You’ll explore three major tools:
GitHub Copilot for code generation, refactoring, and reviews
Tabnine for personalized completions and chat
Amazon Q for team collaboration, commands like /dev and /transform, and secure development
Will I learn how to write effective prompts for coding AI?
Yes! You’ll gain practical experience designing prompts to improve AI accuracy, context awareness, and overall performance in real-world coding tasks.
What makes this course different from other AI or coding courses?
This course focuses on practical, developer-oriented AI usage—not theory or model training. You’ll build real software components with AI as your coding assistant.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.