Generative AI Tools for Modern Software Engineering

Übersicht

This program offers a structured journey into the transformative world of AI-powered code understanding, quality assurance, and intelligent development workflows. Designed for developers, software engineers, and technical leads, this course empowers you to leverage cutting-edge AI tools for efficient code navigation, review, debugging, security, and optimization.

By the end of this program, you will be able to:

- Analyze and explore large codebases quickly with AI tools for faster understanding and onboarding. - Review and evaluate code automatically to ensure high-quality, reliable, and maintainable software. - Create, refactor, and debug code efficiently using intelligent AI-powered assistants. - Secure applications by detecting vulnerabilities, managing dependencies, and enhancing code safety. - Optimize and improve performance with AI-driven profiling, tuning, and resource management tools. This program is ideal for software engineers, AI professionals, and tech leads aiming to enhance their coding workflows with AI.

A foundational understanding of programming concepts, version control, and basic software development practices is recommended. Join us to unlock the power of AI in software engineering and transform the way you navigate, build, and maintain code.

Lehrplan

• AI for Code Understanding and Quality
This module explores AI-powered tools for code navigation, understanding, and quality improvement. Learners gain hands-on experience with tools like Cursor AI, CodeSee, Sourcegraph, and Qodo to analyze codebases, perform reviews, detect issues early, and enhance software reliability.
• AI-Powered Code Creation and Debugging
This module explores AI-powered code creation and debugging, focusing on intelligent code generation, optimization, and problem-solving. Learners will work with tools like Codeium, Refact AI, Trae, and Cody AI to write efficient code, automate refactoring, and enhance debugging processes. The module also covers ethics, reliability in AI-generated code, and practical techniques for error detection and resolution.
• AI for Secure, Optimized, and Collaborative Development
This module explores AI-driven secure, optimized, and collaborative development using tools like Snyk, DeepSource, Codacy, CodeAnt, Minware, Grit.io, mabl, and Katalon. It covers vulnerability detection, secure coding, performance optimization, resource management, workflow automation, and enhanced team collaboration with AI.
• 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.

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Unterrichtet von

Edureka

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Fachgebiete

Computer Science