Generative AI Application Development: Build and Deploy LLM Solutions

Generative AI is transforming how we build software, but moving from simple prompts to production-ready applications requires a solid understanding of the underlying architecture. This course guides you through the entire lifecycle of designing, building, and deploying intelligent AI systems. You will transition from basic programming concepts to constructing sophisticated, context-aware applications. By reading detailed explanations, studying structured code examples, and completing written exercises, you will gain the practical skills needed to develop autonomous workflows and deploy local and cloud-based language model solutions. What you'll learn: Understand the foundational concepts of deep learning, transformer architectures, and large language models; Build context-aware applications using LangChain and Retrieval-Augmented Generation (RAG) patterns; Configure autonomous multi-agent workflows using CrewAI and orchestration tools; Design secure and efficient APIs for your AI models using FastAPI; Deploy containerized AI applications using Docker and modern cloud deployment strategies; Apply prompt engineering best practices and evaluate model outputs for accuracy and safety. The course begins with essential AI terminology and foundational concepts before moving step-by-step through vector databases, agentic workflows, and cloud deployment. You will learn through clear, written explanations and code walkthroughs designed to build your confidence. This course is designed for aspiring developers, software engineers, and tech enthusiasts who want to enter the field of Generative AI, with no prior machine learning experience required. Start reading today to build your first production-ready Generative AI application.