Introduction to Computational Thinking and Data Science
By   |  March 04, 2017

This MIT course 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 you’ll learn:

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

Details:

  • Length: 10 weeks
  • Effort: 15 hours per week
  • Price: Free
  • Add a Verified Certificate for $49
  • Institution: MITx
  • Subject: Computer Science
  • Level: Intermediate
  • Languages: English
  • Video Transcripts: English

© HPC Today 2017 - All rights reserved.

Thank you for reading HPC Today.

Express poll

Do you use multi-screen
visualization technologies?

Industry news

S01-170208

Brands / Products index

S01-170220