The course provides a comprehensive exploration of how generative AI is reshaping software development by accelerating coding, improving debugging, and enhancing automation. It is designed for aspiring software engineers, developers, and professionals who want to integrate AI into modern development workflows to build efficient, scalable, and error-free applications.

You will explore the role of large language models (LLMs) like GPT, Gemini, and LLaMA in coding tasks, software testing, and project automation. The course begins with foundational AI concepts—machine learning, deep learning, and generative models—before diving into practical applications of code generation, prompt engineering, and debugging. Hands-on labs and exercises guide you through AI-powered developer tools such as GitHub Copilot, ChatGPT, and CodeWhisperer. You will also examine advanced AI topics including embeddings, retrieval-augmented generation (RAG), and fine-tuning to customize AI models for specific development needs. Ethical considerations, human-AI collaboration, and the future of AI in engineering are also covered. By the end of this course, you will be able to: - Apply generative AI to accelerate coding, debugging, and software testing. - Use AI-powered tools like Copilot, ChatGPT, and CodeWhisperer to improve productivity. - Implement advanced AI methods such as embeddings, RAG, and fine-tuning. - Evaluate ethical, collaborative, and practical challenges of AI in software engineering.