Linear Algebra for Data Science Using Python
Beginner
67 Lessons
10h
Certificate of Completion
Takeaway Skills
Learning the intricate concepts of linear algebra from scratch
Working knowledge of various linear algebra techniques using Python
A visual understanding of concepts such as vector space, spans, and subspace with animations
Familiarity with valuable concepts like fields, eigenspaces, diagonalization, and SVD
An understanding of how linear algebra concepts build the most useful tools in data science, such as neural networks
The ability to apply linear algebra concepts to real-world problems through coding exercises and practical projects
Course Overview
Linear algebra is a fundamental pillar of data science. In advanced models in data science, like neural networks, the inputs and transformations are based upon vectors, matrices, and tensors which require a reasonable understanding of linear algebra to get the desired results. It is elegant and the most applied mathematics under the umbrella of data science. This course teaches linear algebra with a focus on data science. This course encompasses several engaging illustrations, including static images and a...Show More
Course Content
Introduction
Linearity
Matrices
Solving Linear Systems
Singularity
Linear Regression and Least Squares
11 Lessons
Vector Space
12 Lessons
Vector Spaces of a Matrix
5 Lessons
Singular Value Decomposition: SVD
3 Lessons
Learning to Find Discriminative Null Space for Face Recognition
Project
How You'll Learn
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Built-in assessments let you test your skills. Completion certificates let you show them off.