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 desir...Show More
Course Content
Introduction
1 Lesson
Linearity
11 Lessons
Matrices
5 Lessons
Solving Linear Systems
12 Lessons
Singularity
7 Lessons
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
You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.
Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.
Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.
Built-in assessments let you test your skills. Completion certificates let you show them off.