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.
Integral Calculus and Numerical Analysis for Data Science
This course is part of Expressway to Data Science: Essential Math Specialization
Instructors: James Bird
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(92 reviews)
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What you'll 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.
Skills you'll gain
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There are 4 modules in this course
Explore the notion of area under a curve, how that relates to the integral and compute basic integrals.
What's included
5 videos1 reading4 assignments
Introduction to Numerical Analysis using 2 root-finding methods.
What's included
2 videos2 assignments
Explore general matrix decomposition, as well as a specialized and useful version called Singular Value Decomposition.
What's included
7 videos1 assignment
We will learn a core calculus concept called partial derivatives, as well as delving into directional derivatives and their usefulness in higher level statistics.
What's included
5 videos1 assignment
Instructors
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Recommended if you're interested in Math and Logic
University of Colorado Boulder
University of California, Irvine
University of Pennsylvania
Johns Hopkins University
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Taking this course by University of Colorado Boulder may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
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Reviewed on May 30, 2024
This was an excellent course. Covered some very technical aspects of both derivatives and linear algebra cleanly, and the quizzes made sense.
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