Probability and Statistics in Data Science using Python
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.Created by: The University of California, San Diego
Level: Advanced
Related Online Courses
Learn data literacy online using R programming What is data literacy and why is it important? In this data literacy course, you will learn how to become data literate. This will be accomplished by... more
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in thi... more
Linear regression is commonly used to quantify the relationship between two or more variables. It is also used to adjust for confounding. This course, part ofourProfessional Certificate Program in... more
In this course, part of our Professional Certificate Program in Data Science,you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding... more
Analytical models are key to understanding data, generating predictions, and making business decisions. Without models it’s nearly impossible to gain insights from data. In modeling, it’s ess... more
Powered by
