Course Catalog
3 courses across 12 AI domains
Featured Courses
Python for Machine Learning
Master Python fundamentals and essential libraries for ML including NumPy, pandas, and scikit-learn.
Mathematics for Machine Learning
Build the mathematical foundation you need: linear algebra, calculus, probability, and statistics.
Machine Learning Fundamentals
Supervised and unsupervised learning, model evaluation, feature engineering, and real-world ML pipelines.
Deep Learning with PyTorch
Neural networks, CNNs, RNNs, and transfer learning. Build and train deep models from scratch.
Transformer Architecture Deep Dive
Understand attention mechanisms, build transformers from scratch, and explore BERT, GPT, and beyond.
Large Language Models & GenAI
Master LLM architecture, prompt engineering, RAG, fine-tuning, agents, and production deployment.
All Courses
Prompt Engineering Mastery
Advanced prompting techniques: chain-of-thought, few-shot, constitutional AI, and systematic evaluation.
Large Language Models & GenAI
Master LLM architecture, prompt engineering, RAG, fine-tuning, agents, and production deployment.
Building RAG Applications
Vector databases, embeddings, chunking strategies, hybrid search, and production RAG systems.