Vector Databases and Embeddings
Semantic search and retrieval with pgvector, Pinecone and FAISS.
ML Engineer
Semantic search and retrieval with pgvector, Pinecone and FAISS.
From attention heads to GPT — the architecture behind modern AI.
Function calling, Model Context Protocol servers and safe integrations.
Build, train and export production models with Keras.
Whisper, real-time speech-to-text and natural text-to-speech.
MDPs, Q-learning, policy gradients and RLHF basics.
Image analysis, document understanding and multimodal prompts.
Churn, pricing, fraud, forecasting — a portfolio in one course.
Chains, retrieval, agents and deployment with the most-used LLM framework.
How image generators work — and how to train small ones.
LoRA, QLoRA and instruction tuning on open models.
Evals, golden sets, LLM-as-judge and regression testing for AI products.
Tensors, autograd, CNNs, RNNs and training loops from scratch.
From FAQ bot to a grounded assistant with handoff to humans.
Tool calling, planning loops and memory — no framework required.