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Essential Linear Algebra for Data Science
  • Level Professional
  • Duration 8 hours
  • Course by University of Colorado Boulder
  • Offered by

About

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 Pădureț on Unsplash.com

Modules

Introduction

    • 3 Videos
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3 Videos

  • Introduction to the Course
  • Linear System and Definition
  • Three Solution Options and Coordinate System Visualization

Matrices and Gaussian Elimination

    • 6 Videos
    • 1 Assignment
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1 Assignment

  • Practice - Linear System -> Matrix Format

6 Videos

  • Linear System -> Matrix (Coefficient and Augmented)
  • Rules of G.E. and Solving a Linear System
  • G.E. Intuition and Simple Example
  • G.E Example - Single Solution Part 1
  • G.E Example - Single Solution Part 2
  • G.E Example - Single Solution Part 3 + Meaning

Advanced G.E. with Examples

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • LS -> Matrix + G.E. Full Question Quiz

4 Videos

  • G.E. Example - Infinite Solutions
  • G.E. Example - No Solutions
  • G.E. Advanced Example - Part 1
  • G.E. Advanced Example - Part 2

Introduction to Matrix Algebra + Sum + Scale

    • 2 Videos
    • 1 Assignment
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1 Assignment

  • Quiz on Matrix Algebra Sum + Scale

2 Videos

  • Matrix Algebra Sum
  • Matrix Algebra Scale + Identity Overview

Matrix Multiplication

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Matrix Multiplication

4 Videos

  • Matrix Multiplication + Small Example
  • Matrix Multiplication - General Rules
  • Matrix Multiplication Example
  • Identity Matrix + Example

Vectors and Linear Combinations

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Why do we use matrices and vectors and not just one?

4 Videos

  • Introduction to Vectors + Coordinates
  • Introduction to Linear Combinations
  • Linear Combinations
  • Linear Combinations Example

Linear Independence

    • 7 Videos
    • 1 Assignment
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1 Assignment

  • Quiz on Linear Independence

7 Videos

  • Span
  • Span Example
  • Ax = b
  • Linear Independence
  • Linear Independence Example Part 1
  • Linear Independence Example Part 2
  • Columns of a Matrix Being Linearly Independent

Linear Transformations and Matrix Inverse

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Quiz on Transformations and Inverse

4 Videos

  • Linear Transformations
  • Linear Transformations Example
  • Matrix Inverse
  • Matrix Inverse Example

Determinants

    • 5 Videos
    • 1 Assignment
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1 Assignment

  • Find the Determinant of a 2x2 Matrix

5 Videos

  • Determinant Intro and 2x2 Example
  • Inverse of 2x2 Matrix - Quick Method
  • Determinant of 3x3 Matrix - Overview
  • Determinant of 3x3 Matrix - Example with 1st Row
  • Determinant of 3x3 Matrix - Example with 2nd Row

Eigenvalues and Eigenvectors

    • 3 Videos
    • 2 Assignment
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2 Assignment

  • Find Eigenvalue then Eigenvector of a Matrix (2x2)
  • Find Eigenvalue then Eigenvector of a Matrix (3x3)

3 Videos

  • Eigenvalue and Eigenvector - Overview
  • Finding Eigenvector if Given Eigenvalue
  • Characteristic Polynomic - Finding Eigenvalues

Important Final Concepts

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Important Final Concepts

4 Videos

  • Transpose and Inner (Dot) Product
  • Norm (Length) of a Vector
  • Unit Vector Creation
  • Distance Between Two Vectors

Orthogonality, Projections and Least Squares

    • 5 Videos
    • 1 Assignment
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1 Assignment

  • Finding Least Squares Solutions

5 Videos

  • Orthogonal Vectors
  • Orthogonal Projections Part I
  • Orthogonal Projections Part II
  • Least Squares Overview
  • Least Squares Example

Final Exam

    • 1 Assignment
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1 Assignment

  • Final Exam

Auto Summary

"Essential Linear Algebra for Data Science" is a focused and approachable course tailored for those eager to enter the field of Data Science but who might lack a strong mathematical foundation. This course eliminates the intimidation of complex proofs and concentrates on the core concepts of Linear Algebra that are crucial for data science applications. It serves as a direct pathway to understanding key ideas necessary for a career in Data Science. Offered by Coursera and designed to complement CU Boulder's Master of Science in Data Science (MS-DS) program, this course is an excellent preparatory step for those aiming to tackle Statistical Modeling for Data Science Application. The content is structured to be engaging and accessible, making it perfect for learners who have traditionally found math challenging. With a professional-level designation, the course spans 480 hours and is available through both Starter and Professional subscription options. Whether you're a beginner looking to build a strong foundational knowledge or a professional seeking to refine your skills, this course promises a comprehensive and enjoyable learning experience in the domain of Maths & Statistics.

James Bird
Instructor

James Bird