Learning Paths

Python Programming Fundamentals

Introduction to Large Language Models

Python for LLM Workflows: Tooling and Best Practices

Prompt Engineering and LLM Application Development

Introduction to LLM Agents

Getting Started with Retrieval-Augmented Generation (RAG)

FastAPI for ML Model Deployment

Docker and Containerization for ML Projects

Practical Quantization for Large Language Models

Introduction to LLM Red Teaming

Linear Algebra Fundamentals for Machine Learning

Calculus Fundamentals for Machine Learning

Probability & Statistics Fundamentals for Machine Learning

Python Programming Fundamentals

Introduction to Neural Networks

Getting Started with PyTorch

Introduction to Transformer Models

Advanced Transformer Architecture

Introduction to Diffusion Models for Generative AI

Advanced PyTorch

How To Build A Large Language Model

Python Programming Fundamentals

Getting Started with Git

Docker and Containerization for ML Projects

Introduction to Data Engineering

Introduction to MLOps

Data Versioning and Experiment Tracking for Machine Learning

Introduction to Machine Learning Deployment

Monitoring and Managing ML Models in Production

MLOps for Large Models (LLMOps)

Deploying Quantized LLMs for Efficient Inference

Deploying Diffusion Models at Scale