MITEECS6.0002
Introduction to Computational Thinking and Data Science
Second half of the intro sequence. Plotting, simulations, sampling, statistics, machine learning intro. Pairs with Guttag's book chapters 10-19.
Syllabus
- Week 1
Optimisation and the knapsack problem
Guttag ch. 14
- Week 2
Decision trees and dynamic programming
ch. 15
- Week 3
Graph models
ch. 16
- Week 4
Stochastic thinking; random walks
ch. 17
- Week 5
Monte Carlo simulation; sampling
ch. 18
- Week 6
Inferential statistics; confidence intervals
ch. 19
- Week 7
Experimental data and regression
ch. 20
- Week 8
Machine learning — clustering and classification
ch. 22–23
