Linear Algebra for Data Scientists

Course Overview

This self-paced course is composed of eight modules that include a series of videos, practice opportunities, and required module quizzes. There are two required course exams. 

• Each topic begins with a lecture video, that teaches you the concept and gives you the skills you need to complete assigned problems associated with that topic.
• The guided example videos show an instructor demonstrating how to work through example problems.
• The final video type has practice problems meant for you to work through on your own before watching the instructor solve the problem.
• All the materials you will need to complete the course are included within the course modules.

Use each of these types of videos to learn the concepts and practice completing problems to help reinforce your learning of the concepts and prepare for required quizzes and exams. 

Learning Outcomes

Upon successful completion of this course, you will be able to:

• Perform various operations on vectors, including adding, subtracting, scalar multiplication, and finding the magnitude.
• Apply the formulas for computing the dot product and the cross product.
• Use the dot product to find the projection, or “shadow,” of one vector on the other.
• Determine if a set of vectors forms a basis for a vector space.
• Create new matrices based on given instructions.
• Apply the algebraic properties of matrices that are essential for solving linear systems of equations.
• Select a method to solve systems of linear equations. 
• Use matrices to transform a vector space.

Course Duration

This course is self-paced, and the approximate time to complete the eight course modules is 35 hours. You should plan to complete the course within 8 weeks, completing a module each week. 

Note: Your enrollment will be limited to 180 days, and the countdown of days to complete begins the day you enroll in the course. 

Certificate of Completion

Upon satisfactory completion of Linear Algebra for Data Scientists, you will receive a certificate of completion that will satisfy the linear algebra prerequisite for the M.S. in Data Science program. Satisfactory completion is based on a score of 85% or higher on the eight required quizzes and both exams. Participants will be permitted to retake each exam once should they not score 85% or higher on their first attempt.