Overview

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.

Syllabus

GitHub Copilot for Software Developers

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.

Tabnine AI for Software Developers

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.

Mastering Amazon Q for Developers

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.

Course Wrap-Up and Assessment

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.