About this course

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.

At a Glance:
Institution: UCSanDiegoX
Subject: Data Analysis & Statistics
Level: Advanced
Prerequisites:
The previous coursein the MicroMasters program: DSE200x
Undergraduate level education in:
Multivariate calculus
Linear algebra
Language: English
Video Transcript: English
Associated programs:
MicroMasters® Program in Data Science
Associated skills:Random Variables, Jupyter, Data Science, Python (Programming Language), Probability And Statistics