Introduction to Computational Thinking and Data Science

6.00.2x is the second course in MITx's introductory sequence, following Introduction to Computer Science and Programming Using Python. It teaches how to use computation to reach a range of goals and gives a short introduction to many topics in computational problem solving. The course is aimed at students with some Python programming experience and a rudimentary understanding of computational complexity, and expects you to spend much of your time writing programs that implement the ideas covered, such as simulating a robot vacuum cleaning a room or modelling the population dynamics of viruses and drug treatments in a patient. Topics listed are advanced programming in Python 3, the knapsack problem, graphs and graph optimisation, dynamic programming, plotting with pylab, random walks, probability and distributions, Monte Carlo simulations, curve fitting and statistical fallacies.

It runs instructor-paced over an estimated 9 weeks at 11 to 13 hours per week. Auditing is free and includes the course and its materials; the certificate track, listed at $149, unlocks graded assignments and exams and an MIT certificate on completion. OpenCourseWare publishes the classroom version of the same material as 6.0002.