This comprehensive Generative AI for Developers course is designed to equip software engineers and aspiring AI developers with the practical skills needed to build modern AI-powered applications. It focuses on hands-on development using large language models (LLMs), AI frameworks, and vector database technologies.

The course begins with core concepts of Generative AI and how large language models such as GPT, Gemini, and Llama process and generate human-like text. Developers will learn how these models work under the hood, including tokenization, embeddings, and transformer architectures.

Next, the course introduces prompt engineering techniques to effectively communicate with AI models and optimize responses for different use cases. Learners will also explore Retrieval-Augmented Generation (RAG), which allows AI systems to retrieve external knowledge and produce more accurate, context-aware outputs.

A major part of the course focuses on building AI applications using tools like LangChain and integrating vector databases such as Pinecone or similar systems for semantic search and memory. Students will also learn how to design and deploy AI agents and real-world applications like chatbots, document assistants, and automation tools.

By the end of the course, learners will be able to confidently design, build, and deploy scalable Generative AI applications using industry-standard to