All degrees

Data Science

Statistics, databases and machine learning: how to turn data into decisions that hold up.

  1. 01Programming fundamentalsValues and types, memory, control flow, functions, recursion, lists and strings, errors and tests: the first programming course of any CS degree.
  2. 02Statistics and probabilityFrom averages and dice to Bayes, the normal curve, confidence intervals, p-values and regression: the maths for reasoning about data honestly.
  3. 03Discrete mathematicsLogic, proof, sets, counting, recurrences, graphs and number theory: the mathematics that every algorithm, database and cipher is built on.
  4. 04DatabasesFrom Codd's relational model to SQL, normalisation, transactions, indexes and NoSQL: how data is modelled, queried and kept correct under load.
  5. 05Data structures and algorithmsBig-O, lists, stacks, queues, hash tables, trees, heaps, sorting and graphs: how to store data and how fast you can work with it.
  6. 06Machine learningLoss functions, gradient descent, logistic regression, regularisation, trees, clustering, backpropagation and cross-validation, with the maths worked out.