Develop Generative AI Applications: Get Started

Overview

Get ready to power up your resume with the GenAI development skills employers need. During this course you’ll explore core prompt engineering strategies—like in-context learning and chain-of-thought—and create and manage robust prompt templates. Plus, you’ll follow best practices to handle common errors and experiment with different LLMs and configurations to strengthen your outputs. You’ll then dive deeper into LangChain, mastering chains, tools, and agents to create smarter, more responsive applications. Through interactive labs, you’ll build a complete generative AI app using Python that accepts user input and processes it through your backend prompt logic. Plus, you’ll explore web-based interfaces using tools like Flask and Gradio, developing real-time user experiences powered by LLMs. By the end, you’ll have the job-ready skills and demonstrable practical experience employers look for to design and implement full-stack GenAI apps that solve real-world problems. Sound good? Enroll today!

Syllabus

Foundations of Generative AI and Prompt Engineering

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.

Introduction to LangChain in GenAI Applications

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.

Build a Generative AI Application with LangChain

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.