Course Catalog

1 courses across 12 AI domains

All Programming Mathematics ML Fundamentals Deep Learning NLP Computer Vision LLMs & GenAI MLOps Reinforcement Learning System Design Ethics & Safety AI for PMs

Featured Courses

Master Python fundamentals and essential libraries for ML including NumPy, pandas, and scikit-learn.

Build the mathematical foundation you need: linear algebra, calculus, probability, and statistics.

Supervised and unsupervised learning, model evaluation, feature engineering, and real-world ML pipelines.

Neural networks, CNNs, RNNs, and transfer learning. Build and train deep models from scratch.

Understand attention mechanisms, build transformers from scratch, and explore BERT, GPT, and beyond.

Master LLM architecture, prompt engineering, RAG, fine-tuning, agents, and production deployment.

Deploy, monitor, and maintain ML systems. Docker, Kubernetes, CI/CD, experiment tracking, and drift detection.