From mathematical and computing foundations to machine learning and advanced AI. ≈ 10 h a week over 40 weeks.
Write your first Python programs, work with files, the web and SQL databases, and build a critical understanding of data and AI.
Project: The Python for Everybody capstone (collecting, storing and visualizing web data), then the Fundamentals of Computing final exam.
Open the semesterS2 · 191 hAcquire the continuous mathematical tools on which all of statistics and machine learning depend.
Project: The Mathematics for Engineers capstone: numerical computation of the flow past a cylinder (Kármán vortex street).
Open the semesterS3 · 173 hLearn to prove, count and reason about graphs, then design and analyze efficient algorithms.
Project: The UCSD Delivery Problem project: solve a travelling salesman problem and compare heuristics.
Open the semesterS4 · 269 hBuild a solid probabilistic foundation, then learn to estimate, test and model.
Project: A complete study in R: frame a question, fit a linear model or GLM, check the residuals and write a reproducible report.
Open the semesterS5 · 191 hPrepare real-world data at scale in Python, then train and evaluate supervised and unsupervised models.
Project: The Data Wrangling with Python final project, then a complete predictive model on the same data.
Open the semesterS6 · 262 hMaster the three main pillars of modern AI: Bayesian inference, deep neural networks and reinforcement learning.
Project: Two capstones: Bayesian Statistics (a complete Bayesian analysis of a dataset) and A Complete Reinforcement Learning System (an end-to-end agent).
Open the semesterFrom mathematical and computing foundations to machine learning and advanced AI.