Mastering Generative AI: LLM Apps, LangChain, RAG & Chatbots

Master Generative AI with hands-on Large Language Models (LLMs), ChatGPT, LangChain, RAG, vector databases & real-world projects.

What you'll learn

Requirements

• Basic knowledge of Machine Learning is beneficial but not mandatory.
• Familiarity with Python is helpful, but key concepts are covered from scratch.
• A computer with internet access to run notebooks and tools.

Course description

"Gen AI Masters 2025 — From Python To LLMs and Deployment" is a comprehensive program designed for both beginners and experienced developers who want to master Generative AI and Large Language Models (LLMs).

You'll start by strengthening your Python programming skills and quickly move into core AI and NLP concepts. Learn how to manipulate data using popular libraries such as Pandas and NumPy, then dive into Natural Language Processing (NLP) techniques for text cleaning, feature extraction and modeling with libraries like NLTK and spaCy.

The course covers deep learning foundations and the architecture of Transformer models, enabling you to understand how modern LLMs work under the hood. You will explore training and fine-tuning techniques including PEFT, LoRA and QLoRA to adapt large models to specific tasks.

A major focus of the course is Retrieval-Augmented Generation (RAG). You'll learn how to combine information retrieval with generative models to build powerful AI systems. Evaluation methods such as RAGAS, BLEU, ROUGE, BARScore and BERTScore are introduced to measure the quality of your AI outputs.

You will also master prompt engineering, designing effective prompts that control model behavior and improve results. Vector databases such as FAISS are used to store and retrieve embeddings, allowing you to create scalable search and RAG solutions.

The course culminates in a capstone project where you build a real-world Generative AI solution, applying everything you've learned from Python and NLP to LLMs, RAG and deployment.

Capstone projects & use cases

• AI Career Coach: A personalized chatbot that guides users in career development and job search strategies using real-time data and AI insights.
• AI-Powered Automated Claims Processing: An intelligent system that automates data extraction and decision-making for insurance claims.
• Chat Scholar + Essay Grading System: A chatbot that assists students with writing and provides AI-driven grading and feedback.
• Research RAG Chatbot: A research assistant that retrieves relevant academic content and generates concise summaries.
• Sustainability Chatbot (GROK AI): An eco-focused chatbot that educates users on sustainable practices and actionable steps to reduce carbon footprint.

You can also bring your own project idea; the course is designed to help you adapt the concepts to your specific use case.

Course content

27 sections · 207 lectures · 47h 7m total length

Instructors

Student reviews

Who this course is for

• Individuals passionate about AI and Machine Learning who want to expand their skills in Generative AI.
• Professionals seeking to build and deploy Generative AI models in business or product environments.
• Developers interested in integrating advanced AI capabilities into their applications.
• Anyone who wants to understand LLMs, RAG and prompt engineering in depth.