Teaching

Slides, theory notes, exercises, and solutions are public, in Spanish. Most instructors publish the problems; I publish the solutions too.

Universidad Científica del Sur Principios de Big Data - DICDASA 304 Postgraduate Diploma in Health Data Science (DICDASA). Executive-level course, 20 h across 4 live sessions, taught to physicians, clinical managers, and hospital administrators without assuming programming
Lecturer · 2025–present
  1. Fundamentals of Big Data & AI in health slides
  2. Data architectures, distributed systems & the cloud slides
  3. Applied & responsible AI in clinical settings slides
  4. Leading data projects - AI Charter capstone slides
Universidad Científica del Sur Machine Learning & AI Methods in Health - DICDASA 301 Second course I teach in the diploma: how learning methods actually work, and where they fail, for a clinical audience. Slides coming soon.
Lecturer · 2026
  1. Supervised learning - from clinical labels to predictions
  2. Unsupervised learning - patient segmentation & structure discovery
  3. Transfer learning - reusing pretrained models on small clinical datasets
  4. Evaluation, generalization & failure modes in clinical AI
iDeepBrain LangGraph from zero - my open GenAI course 16 classes building AI agents with LangGraph, LangChain, and Gemini, up to a multi-agent capstone. Materials go public as I teach them.
In progress · 2026
BREIT & MIT IDSS Machine Learning, Probability & Data Analysis in Social Science MIT MicroMasters in Statistics & Data Science - partnership between MIT IDSS and Aporta (Breca Group), delivered in Peru. 13 review sessions for MIT 14.310x, everything public: slides, theory notes, a five-level problem bank, and full solutions
TA · 2022–present
  1. Probability foundations & counting (with R) slides theory exercises solutions
  2. Conditional probability, independence & Bayes slides theory exercises solutions
  3. Random variables & joint distributions slides theory exercises solutions
  4. Expectation, variance & moments slides theory exercises solutions
  5. Special distributions, sample mean & CLT slides theory exercises solutions
  6. Estimators, confidence intervals & hypothesis testing slides theory exercises solutions
  7. Hypothesis testing, complete guide - z/t/χ²/F, two-sample, power slides theory exercises solutions
  8. Causality, randomized experiments & non-parametric regression slides theory exercises solutions
  9. Simple & multivariate linear model slides theory exercises solutions
  10. Regression in practice & omitted-variable bias slides theory exercises solutions
  11. Applied R review & introduction to instrumental variables slides theory exercises solutions
  12. Comprehensive probability review - Q&A session in English slides solutions
  13. Comprehensive inference & regression review - Q&A session in English slides solutions
4Geeks Academy Machine Learning Bootcamp Bootcamp founded in Uruguay - training Latin American professionals in ML and data science
TA · 2022
  1. Probability & statistics
  2. Data analytics & visualization
  3. Applied machine learning
  4. Model evaluation & deployment
CTIC - National University of Engineering (UNI) Machine Learning & Computer Vision Volunteer instruction for undergraduate students at Peru’s leading engineering university
Instructor · 2018–2019
  1. Machine Learning & Deep Learning
  2. Computer vision with Python and C++
  3. Anomaly detection
  4. License plate recognition
  5. Object detection & tracking