Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

University of Colorado Boulder

Integral Calculus and Numerical Analysis for Data Science

University of Colorado Boulder via Coursera

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
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 provide an intuitive understanding of foundational integral calculus, including integration by parts, area under a curve, and integral computation. It will also cover root-finding methods, matrix decomposition, and partial derivatives.

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 ThisisEngineering RAEng on Unsplash.com

Syllabus

  • Area Under The Curve
    • Explore the notion of area under a curve, how that relates to the integral and compute basic integrals.
  • Numerical Analysis Intro
    • Introduction to Numerical Analysis using 2 root-finding methods.
  • Diagonalization & SVD
    • Explore general matrix decomposition, as well as a specialized and useful version called Singular Value Decomposition.
  • 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.

Taught by

James Bird and Jane Wall

Reviews

4.6 rating at Coursera based on 76 ratings

Start your review of Integral Calculus and Numerical Analysis for Data Science

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.