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.

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Generative AI Coding Assistants for Developers
This course is part of Generative AI for Software Engineers & Developers Specialization

Instructor: Edureka
Included with
Recommended experience
What you'll learn
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.
Skills you'll gain
- Generative AI Agents
- Integrated Development Environments
- Maintainability
- DevOps
- CI/CD
- Software Technical Review
- Amazon Web Services
- Software Engineering
- Software Development
- Artificial Intelligence and Machine Learning (AI/ML)
- Generative AI
- Software Documentation
- Test Automation
- Software Architecture
- Collaborative Software
- Secure Coding
- Application Security
- AI Personalization
- Code Review
- GitHub
Details to know

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August 2025
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There are 4 modules in this course
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.
What's included
21 videos7 readings5 assignments4 discussion prompts2 plugins
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.
What's included
16 videos4 readings5 assignments4 discussion prompts1 plugin
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.
What's included
13 videos3 readings4 assignments3 discussion prompts1 plugin
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.
What's included
1 video1 reading2 assignments1 discussion prompt
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Frequently asked questions
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.
More questions
Financial aid available,
¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.