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Introduction to Computational Thinking and Data Science

Introduction to Computational Thinking and Data Science

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(5 customer reviews)
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8.7/10 (Our Score)
Product is rated as #85 in category 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

Instructor Details

Professor Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. He leads the Computer Science and Artificial Intelligence Laboratory’s Data Driven Medical Research Group. The group works on the application of advanced computational techniques to medicine. Current projects include prediction of adverse medical events, prediction of patient-specific response to therapies, non-invasive monitoring and diagnostic tools, and tele-medicine. He has also done research, published, and lectured in the areas of data networking, sports analytics, software defined radios, software engineering, and mechanical theorem proving. Professor Guttag received his bachelors degree in English and his master's in applied mathematics from Brown University. His doctorate is from the University of Toronto. From January of 1999 through August of 2004, Professor Guttag served as Head of MIT’s Electrical Engineering and Computer Science Department. He is a Fellow of the ACM and a member of the American Academy of Arts and Sciences.

Specification: Introduction to Computational Thinking and Data Science

Duration

135 hours

Year

2020

Level

Intermediate

Certificate

Yes

Quizzes

No

5 reviews for Introduction to Computational Thinking and Data Science

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  1. Anonymous

    This course is great if you just want to watch the lectures. The work is awful. It’s not that its hard, because it’s a programming class. It’s more the way it’s run. The TAs are very unhelpful and often delete comments if they view them as revealing too much, without responding to questions. Do not take this course unless you want to watch the lectures.

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  2. Thong Buu Tran

    This course is a second course in CS Foundation XSeries. I took this course last year and again I could say this is one of the most intellectually stimulating class ever. The Psets were challenging and well designed to help students get familiar with data science. There are some prerequisites before taking this class which are familiarity with Python and programming concepts and desire to learn by doing.

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  3. Keshav Gupta

    One of the excellent course that I have completed. All those who are interested in this topic must give this course a try. During the course, you will find it to be interesting and on completion, you will find yourself elevated!

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  4. Dolly Ye

    I love everything about this course.It is the most comprehensive and rigorous beginner cs class online! You will at times struggle with programming assignments but remember,you will emerge with a love for computer science and ability to pick up any new concept.

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  5. Shiraz Suleman

    Really good course however it’s quite difficult and there’s a heavy focus on statistics and machine learning so not recommended for beginners.

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    Introduction to Computational Thinking and Data Science
    Introduction to Computational Thinking and Data Science

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