Data Science, AI & Machine Learning

This section is the hub for data science, artificial intelligence, and machine learning work I do with organizations and learners: open and custom courses, workshops and cohort-style training, and consulting on problem framing, modeling approaches, responsible use of AI, tooling, and how to ship analytics and ML into real workflows—not only slide decks, but paths you can run in production or in the classroom.

The cards below are mostly course and program pages (syllabi, objectives, prerequisites, and stack notes). Together they show the themes I teach and advise on—statistics and experimentation, classical ML, deep learning, NLP, explainability, MLOps-adjacent practice, and domain-flavored tracks—so you can see what is covered, at what depth, and how engagements are structured before you reach out for a tailored engagement.