A nineteen-week path from statistics and Python through classical machine learning, deep learning, generative AI and MLOps — ending with a live, monitored model, not a trained one sitting in a notebook.
Advanced pandas/NumPy, probability and hypothesis testing.
Analytical SQL for sourcing and joining features.
Regression, classification, ensembles and evaluation.
Feature engineering, tuning, SHAP explainability.
Neural networks, CNNs, RNNs, TensorFlow and PyTorch.
Embeddings, vector databases, LangChain, RAG.
FastAPI, Docker, MLflow, production monitoring.
AI copilots, Power BI dashboards, stakeholder storytelling.
One dataset, start to finish — a deployed, monitored model.
Senior Data Scientist & AI/ML Programme Leader, 11 years of experience. Instructor at Berkeley Haas and Imperial College Business School. Every batch — up to 50 learners — taught live, session by session.
Every learner finishes with a deployed, portfolio-ready project — not a certificate for finishing videos.
Full curriculum, week-by-week session plan, capstone tracks and mentor details — sent straight to your inbox and available to download immediately.
Message us on WhatsApp or get in touch — we'll help you confirm this is the right course before you commit to anything.