Probability and Statistics in Data Science using Python
University of California, San Diego via edX
- Provider edX
- Cost Free Online Course (Audit)
- Session Upcoming
- Language English
- Certificate $350 Certificate Available
- Effort 10-12 hours a week
- Duration 10 weeks long
- Learn more about MOOCs
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Overview
The job of a data scientist is to glean knowledge from complex and noisy datasets.
Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.
In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks.
Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL.
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Reviews for edX's Probability and Statistics in Data Science using Python Based on 19 reviews
- 5 stars 16%
- 4 star 0%
- 3 star 5%
- 2 stars 16%
- 1 stars 63%
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Write a review- 1
The programming assignments are also non-intuitive and could be handled much better.
There are much better ways of handling a course like this and I am severely disappointed with this course.
No doubt, the teachers are more than competent but the presentation of the content is just plain boring and not adapted for MOOC at all, like recording a black board in school.
Suggestion for improvement: Split the course in two parts and re-record the content in order to make it more engaging (like the UCSD Python for Data Science course in the same track).
It's a good course since it's designed much like a full-length course that you will experience on-campus... but the instructor really needs to stop doing the presentation only by clicking the slides and moving the mouse around.
But the protocoled exam is terrible. It crashed 10min after it started. I feel all my effort was wasted only due to this terrible exam software provided by third party.
Glad I am not the only one who felt there is way too much content for supposedly "10 hours per week".
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