Instructor: John Guttag
| A collection of Problem Sets for MITx: 6.00.2x Introduction to Computational Thinking and Data Science. I took this online course on edX platform during March-May, 2021. Each of the Problem Set deals with a real-world problem such as spreading of viruses in a patient, modelling of temperature in different areas to find evidence of global warming, etc. Below you can see some interesting visualization of each Problem Set that I solved.🙂 (Certificate of Completion) |
DISCLAIMER: Please do not simply copy the code without trying to solve the problems yourself in the first place. The author reserves all rights but does not be liable in any event (e.g., plagiarism) caused by the use of the program. Remember that one can only learn programming by doing it. Have fun coding!😃
This course is the second part of MITx's Computational Thinking using Python XSeries Program
Topics covered include:
- Advanced programming in Python 3
- Knapsack problem, graphs and graph optimization
- Dynamic programming
- Plotting with the
pylabpackage - Random walks
- Probability, distributions
- Curve fitting
- Statistical fallacies
- Plotting with the pylab package
- Stochastic programming and statistical thinking
- Monte Carlo simulations
greedy and brute-force algorithms for cow transport
simulation of robot vacuum(s) cleaning a ractangular room
modelling of viruses population dynamics and drug treatments in a patient's body
analyzing and visualizing climate change in terms of temperature using regression models
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Temperature of a specific date (i.e., Jan 10th in this case) in Boston from 1961 to 2005
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Average annual temperature in Boston from 1961 to 2005
If you have any question or suggestion, feel free to contact me at huaming.huang.tw@gmail.com. Contributions are also welcomed. Please open a pull-request or an issue in this repository.