Building Generative AI Apps with LangChain and Hugging Face

Generative AI is transforming how we build software, but connecting large language models to real-world data requires the right tools. This text-based course guides you through the core concepts of LangChain and Hugging Face to construct intelligent, context-aware applications. You will transition from understanding basic AI terminology to building and deploying functional generative AI applications. Through clear written explanations and structured code analysis, you will master the mechanics of prompt engineering, model integration, and external data retrieval. What you'll learn: - Understand the foundational principles of generative AI, large language models, and transformer architectures. - Integrate open-source models from Hugging Face into your development environment. - Build robust AI workflows, chains, and agents using the LangChain framework. - Develop Retrieval-Augmented Generation (RAG) pipelines to connect AI models with external vector databases. - Apply modern prompt engineering techniques to optimize model outputs and system reliability. - Configure and deploy generative AI applications for real-world production environments. The journey begins with essential AI concepts and environment setup before progressing to hands-on code walkthroughs for chat interfaces, content generators, and document search systems. You will read detailed conceptual breakdowns and study structured Python code snippets to build your practical skills. This course is designed for software developers, data enthusiasts, and tech professionals who are new to AI orchestration. A basic understanding of Python is recommended, but no prior machine learning experience is required. Start reading today to build your first intelligent AI application.