Introduction to Computational Thinking and Data Science

6.00.2x will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving . 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