Udemy - Complete Linear Algebra for Data Science and Machine Learning 2020-2 - Download

Description

Complete Linear Algebra in Data Science, Software Engineering and Linear Algebra educational video series can be named. In fact, in this course you will be introduced to a very thorough and complete concept of linear algebra used in data science and machine learning. The entire content and teaching of this course is presented to students in the simplest form possible. At the end of the sessions, there are various tests to help students improve their basic skills.

This course also assumes that your students have no prior knowledge and experience. So all the content, step by step, you will be trained. The approach, of course, can also be learned in accordance with practice, with realistic and practical help. This course is for developers, very suitable data, artificial intelligence, learning, machine, learning and ... computer graphics and ... programming etc.

Occasions for teaching the course:

Learning and in-depth study of the basics of linear algebra
Familiarization with the concept and basics of Matrix and its use in projects
Learning activities in a Matrix unit, such as scale transfer
Learn how to perform operations on two matrices, such as matrix multiplication
Learn how to solve systems of linear equations using matrix and matrix inverse
And...

Data Science Profile, Course, Complete, Linear Algebra

Language: English
Duration of time : 17:53:59
Number of courses: 210
Supervisor: Kashif A.
File format: mp4

This course completes linear algebra in data science

course content
210 lectures 17:53:59

Welcome and introduction
1 lecture 02:43

Basics of matrices
6 lectures 32:28

Matrix Basics (continued)
12 lectures 01:18:49

Matrices and systems of linear equation
7 lectures 46:36

Matrix algebra and operations
5 lectures 21:24

Matrix determinant
4 lectures 20:43

The inverse of a matrix
7 lectures 46:30

Properties of determinants
6 lectures 14:57

*** OPTIONAL: Introduction to Vectors
11 lectures 52:30

Vector spaces
9 lectures 40:04

Subspace and null space
7 lectures 24:25

Straightness and width sets
5 lectures 20:02

Linear dependence and independence
7 lectures 31:54

Base and dimension
6 lectures 17:54

Eigenvalues and eigenvectors
3 lectures at 22:20

Basic Algebra Concepts (Additional Lessons)
78 lectures 04:41:52

Congratulations and bonus material
36 lectures 05:18:44

Prerequisite courses

Passion to learn about matrices and vectors
Ability to perform basic mathematical operations (+, -, x, ÷) with numbers and fractions
Knowledge of how to solve a linear equation (e.g. find x 3x-4=11)
Understanding basic algebra concepts such as powers and roots, simplifying fractions, factoring, solving equations, and graphing.
You only need to know basic math and algebra to complete this course.
And the best thing is that most of the aforementioned prerequisite topics have been completed within the course 🙂