Introduction to Computational Thinking and Data Science
Computational Thinking using Python,
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
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| Rating | 4.5★ based on 34 ratings |
|---|---|
| Length | 9 weeks |
| Effort | 9 weeks, 14–16 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $75 |
| From | Massachusetts Institute of Technology, MITx via edX |
| Instructors | Eric Grimson, John Guttag, Ana Bell |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science |
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What people are saying
help students get familiar
The Psets were challenging and well designed to help students get familiar with data science.
content 5* instructor 5*++
Content 5* Instructor 5*++ and Provider 5* I am midway to 6.00.1x when I enrolled into 6.00.2x.
formulas almost reads like
I passed it but would like to retake it (kind of barely made it)- however I am not sure if time will permit [school, work, family - maybe is better to do the next one of the series instead of retaking this one] - Prof Guttag's way of teaching brings life to the data analysis concepts - formulas almost reads like a story.
heavy focus on statistics
Really good course however it's quite difficult and there's a heavy focus on statistics and machine learning so not recommended for beginners.
writing simple python programs
After having completed them, I feel confident in writing simple Python programs and have been inspired to take some more advanced courses in computer science.
mit ocw videos also
The youtube and MIT OCW videos also complement this course.
cs foundation xseries
This course is a second course in CS Foundation XSeries.
any new concept
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.
often delete comments
The TAs are very unhelpful and often delete comments if they view them as revealing too much, without responding to questions.
prerequisites before taking
There are some prerequisites before taking this class which are familiarity with Python and programming concepts and desire to learn by doing.
revealing too much
rigorous beginner cs
I love everything about this course.It is the most comprehensive and rigorous beginner cs class online!
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| Rating | 4.5★ based on 34 ratings |
|---|---|
| Length | 9 weeks |
| Effort | 9 weeks, 14–16 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $75 |
| From | Massachusetts Institute of Technology, MITx via edX |
| Instructors | Eric Grimson, John Guttag, Ana Bell |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science |
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