This module introduces the basics of generative AI and provides an overview of the most common tools, frameworks, and models used in AI development. You'll learn fundamental prompt engineering principles that help maximize AI model capabilities through thoughtful input design. Special emphasis is placed on the LangChain framework—its features, benefits, and role in designing and writing AI applications. The module covers practical techniques for creating reusable prompt templates that improve consistency, implementing in-context learning strategies, and optimizing AI responses through iterative prompt refinement.

In this module, you will explore LangChain and its advanced features to build generative AI applications. You’ll learn about each core component of LangChain, how to incorporate them to create complex workflows and introduce generative AI into your applications.

In this module, you’ll build a Flask web app that uses the power of generative AI using LangChain. You’ll learn how to integrate AI into your application, leverage LangChain’s JsonOutputParser to produce structured outputs, and fine-tune prompt engineering to generate actionable JSON responses. Along the way, you’ll compare and evaluate different language models—including Llama 3, Granite, and Mixtral—to discover which best suits your needs.