MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
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.
Course 3 of 3 in the Expressway to Data Science: Essential Math Specialization.
What You Will Learn
- Practice integrating by parts for more complex problems.
- Identify how bisection works after its given an initial guess.
- Diagonalize a matrix by hand.
- Compute the partial derivatives of a function.
Syllabus
WEEK 1
Area Under The Curve
Explore the notion of area under a curve, how that relates to the integral and compute basic integrals.
WEEK 2
Numerical Analysis Intro
Introduction to Numerical Analysis using 2 root-finding methods.
WEEK 3
Diagonalization & SVD
Explore general matrix decomposition, as well as a specialized and useful version called Singular Value Decomposition.
WEEK 4
Partial Derivatives & Steepest Descent
We will learn a core calculus concept called partial derivatives, as well as delving into directional derivatives and their usefulness in higher level statistics.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.