Generative AI with Python

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unlock the power of generative AI by mastering Python and working hands-on with cutting-edge tools and libraries. From building large language models (LLMs) to implementing advanced agentic systems, this course takes you on an in-depth journey through AI development. You’ll explore the essentials of LLMs, model training, parameter tuning, and the integration of advanced techniques like Retrieval-Augmented Generation (RAG) and vector databases. The interactive learning experience ensures you are not just passively absorbing information but engaging with practical coding exercises and real-world applications. The course begins with the foundational setup, including Python, IDEs, and environment configurations, before diving deep into LLMs, multimodal models, and even exploring agent-based systems. You’ll move through advanced topics such as prompt crafting, chaining models, and building intelligent systems with frameworks like crewAI and AG2. The journey concludes with model fine-tuning techniques, including Low-Rank Adaptation (LoRA), that enable you to optimize performance. This course is designed for AI enthusiasts, data scientists, and developers who want to expand their skills in generative AI. It is ideal for anyone with basic knowledge of Python who wants to build AI-driven applications. The course is suitable for those at an Intermediate level with some prior programming experience in Python. By the end of the course, you will be able to design and implement generative AI models, create complex AI workflows using chains and agents, manage vector databases, and fine-tune models to suit specific tasks and domains.