Are you interested in Data Science but lack the math background for it? Has math always been a tough subject that you tend to avoid? This course will teach you the most fundamental Linear Algebra that you will need for a career in Data Science without a ton of unnecessary proofs and concepts that you may never use. Consider this an expressway to Data Science with approachable methods and friendly concepts that will guide you to truly understanding the most important ideas in Linear Algebra. This course is designed to prepare learners to successfully complete Statistical Modeling for Data Science Application, which is part of CU Boulder's Master of Science in Data Science (MS-DS) program. Logo courtesy of Dan-Cristian P膬dure葲 on Unsplash.com
Transpose and Inner (Dot) Product
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Skills You'll Learn
Mathematics, Numerical Analysis, Integrals, Algebra, Derrivatives, Linear Algebra, Matrix Algebra
Reviews
4.4 (169 ratings)
- 5 stars74.55%
- 4 stars9.46%
- 3 stars7.10%
- 2 stars3.55%
- 1 star5.32%
LH
May 10, 2022
Well-explained and comprehensive. I thought it was going to be a rough course but Professor Bird is very thorough and concise in his lectures.
OS
Nov 16, 2022
Outstanding and well-balanced course, great teacher, and an optimal workload. Passed the course with pleasure and highly recommended it.
From the lesson
Projections and Least Squares
In this module we will learn how to compute the determinant of a matrix. Afterwards, Eigenvalues and Eigenvectors will be covered.
Taught By
James Bird
Instructor