Introduction to Computational Thinking and Data Science

John Guttag, Eric Grimson, Ana Bell, MITx

6.00.2x is an introduction to using computation to understand real-world phenomena.

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

What will you learn

  • Plotting with the pylab package
  • Stochastic programming and statistical thinking
  • Monte Carlo simulations

Dates:
  • 16 October 2019
Course properties:
  • Free:
  • Paid:
  • Certificate:
  • MOOC:
  • Video:
  • Audio:
  • Email-course:
  • Language: English Gb

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