Course description
Probability and Statistics in Data Science using Python
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.
Who should attend?
Prerequisites
- The previous coursein the MicroMasters program: DSE200x
- Undergraduate level education in:
- Multivariate calculus
- Linear algebra
Course delivery details
This course is offered through The University of California, San Diego, a partner institute of EdX.
10-12 hours per week
Costs
- Verified Track -$350
- Audit Track - Free
Certification / Credits
What you'll learn
- The mathematical foundations for machine learning
- Statistics literacy: understand the meaning of statements such as "at a 99% confidence level"
Contact this provider
edX
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