Introduction to Computational Thinking and Data Science - Massachusetts Institute of Technology

edX
4.4
4 reviews
  • Both of these courses (6.00.1x and 6.00.2x) are the excellent one's. I would prescribe it to understudies as well as to those too who are working professionally in IT.
    ← | →
  • I had done the 6.00.1x and running with 6.00.2x and they are exceptionally useful for learning python programming dialect and additionally to create computational model for reproducing and actualizing things in physical world. A total decent arrangement for progression of programming abilities and furthermore a significant confirmed declaration you can win through these courses.
    ← | →
  • In case you are in this course to learn writing computer programs, you are at the wrong place. While presenting a couple of all the more programming and software engineering ideas at the outset, the course rapidly transforms into an insights course, utilizing calculation as a recreation instrument. The teacher's absence of eagerness is additionally a major issue. Prof. Guttag addresses in an extremely dreary voice and does not demonstrate any energy in the material. I would not prescribe this course. Still, props to MIT for making some much incredible substance accessible on edX.
    ← | →

Course

Online

Free

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Description

  • Type

    Course

  • Methodology

    Online

  • Duration

    10 Weeks

  • Start date

    Different dates available

6.00.2x is an introduction to using computation to understand real-world phenomena. With an apprenticeship you earn while you learn, you gain recognized qualifications, job specific skills and knowledge and this helps you stand out in the job market.With this course you earn while you learn, you gain recognized qualifications, job specific skills and knowledge and this helps you stand out in the job market.

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

6.00.1x or equivalent (some prior programming experience in Python and a rudimentary knowledge of computational complexity)

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Reviews

4.4
fantastic
  • Both of these courses (6.00.1x and 6.00.2x) are the excellent one's. I would prescribe it to understudies as well as to those too who are working professionally in IT.
    ← | →
  • I had done the 6.00.1x and running with 6.00.2x and they are exceptionally useful for learning python programming dialect and additionally to create computational model for reproducing and actualizing things in physical world. A total decent arrangement for progression of programming abilities and furthermore a significant confirmed declaration you can win through these courses.
    ← | →
  • In case you are in this course to learn writing computer programs, you are at the wrong place. While presenting a couple of all the more programming and software engineering ideas at the outset, the course rapidly transforms into an insights course, utilizing calculation as a recreation instrument. The teacher's absence of eagerness is additionally a major issue. Prof. Guttag addresses in an extremely dreary voice and does not demonstrate any energy in the material. I would not prescribe this course. Still, props to MIT for making some much incredible substance accessible on edX.
    ← | →
100%
4.3
fantastic

Course rating

Recommended

Centre rating

Waqar Akbar

4.5
28/12/2016
What I would highlight: Both of these courses (6.00.1x and 6.00.2x) are the excellent one's. I would prescribe it to understudies as well as to those too who are working professionally in IT.
What could be improved: Nothing.
Would you recommend this course?: Yes

Ritik Jain

4.0
27/12/2016
What I would highlight: I had done the 6.00.1x and running with 6.00.2x and they are exceptionally useful for learning python programming dialect and additionally to create computational model for reproducing and actualizing things in physical world. A total decent arrangement for progression of programming abilities and furthermore a significant confirmed declaration you can win through these courses.
What could be improved: Everything was positive.
Would you recommend this course?: Yes

Chris Chen

4.0
26/12/2016
What I would highlight: In case you are in this course to learn writing computer programs, you are at the wrong place. While presenting a couple of all the more programming and software engineering ideas at the outset, the course rapidly transforms into an insights course, utilizing calculation as a recreation instrument. The teacher's absence of eagerness is additionally a major issue. Prof. Guttag addresses in an extremely dreary voice and does not demonstrate any energy in the material. I would not prescribe this course. Still, props to MIT for making some much incredible substance accessible on edX.
What could be improved: Nothing.
Would you recommend this course?: Yes

David Blackwell

5.0
25/12/2016
What I would highlight: This class and its antecedent, 6.00.1x were my first tastes of programming and computational considering, and I tremendously delighted in two of them. Subsequent to having finished them, I feel certain about composing basic Python programs and have been enlivened to take some more propelled courses in software engineering. I unequivocally prescribe both classes.
What could be improved: N/A.
Would you recommend this course?: Yes
*All reviews collected by Emagister & iAgora have been verified

This centre's achievements

2017

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 8 years

Subjects

  • Computer Science
  • Computational
  • Data science
  • Python
  • 6.00.2x

Course programme

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: Plotting with the pylab package Random walks Probability, Distributions Monte Carlo simulations Curve fitting Knapsack problem, Graphs and graph optimization Machine learning basics, Clustering algorithms Statistical fallacies

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Introduction to Computational Thinking and Data Science - Massachusetts Institute of Technology

Free

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