Solutions for problem sets for MITx: 6.00.2x (Introduction to Computational Thinking and Data Science) MOOC course
COURSE OVERVIEW
This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. You will spend a considerable amount of time writing programs to implement the concepts covered in the course. For example, you will write a program that will simulate a robot vacuum cleaning a room or will model the population dynamics of viruses replicating and drug treatments in a patient's body.
Topics covered include:
Advanced programming in Python 3 Knapsack problem, Graphs and graph optimization Dynamic programming Plotting with the pylab package Random walks Probability, Distributions Monte Carlo simulations Curve fitting Statistical fallacies