What you will learn
- The mathematical foundations for machine learning
- Statistics literacy: understand the meaning of statements such as “at a 99% confidence level”
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.
Before you start
- The previous course in the MicroMasters program: DSE200x
- Undergraduate level education in:
- Multivariate calculus
- Linear algebra
- Instructor-Led: course contains assignments and exams that have specific due dates, and you complete the course within a defined time period.
- Course ends: Feb 22, 2019
Meet Your Instructors
Who can take this course?
Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.