advanced Level Self-Paced Track Certificate Included

Large Language Models & Generative AI

Comprehensive guide to contemporary LLM architectures, high-dimensional vector embeddings, semantic search with Pinecone and ChromaDB, prompt engineering patterns, and autonomous agent loops.

2h 7m total content
5 lessons & projects
Instructor: Atul Jha
Large Language Models & Generative AI

Course Overview

About this Course

Build state-of-the-art applications powered by large language models, retrieval-augmented generation (RAG), and agentic workflows.

Key Competencies You'll Build

Mathematical foundations written from pure first principles
Clean, reproducible PyTorch / Python code without black boxes
Production deployment and low-latency inference patterns
Hands-on capstone portfolio piece ready for GitHub

Course Curriculum

1 chapters • 5 total lessons & checkpoints

ArticleTokenization, Context Windows & High-Dimensional Embeddings
20 minStart →
VideoSystem Prompts, Few-Shot In-Context Learning & Structured Outputs
27 minStart →
ArticleVector Databases, HNSW Indexing & Hybrid Search
25 minStart →
VideoFunction Calling, Autonomous Tool Use & Multi-Agent Routing
30 minStart →
LabInteractive Vector Embeddings & Semantic Search Lab
25 minStart →