machine learning

“Complete Linear Algebra for Data Science & Machine Learning” covers every aspect of the subject from start to finish. With over 200 video lessons, each idea is explained in a simple and easy-to-understand manner. The course includes tests and assignments with solutions to help you check your understanding. Whether you’re a student, professional, or math enthusiast, this course will guide you through the fundamental concepts of Linear Algebra in a fun and approachable way. In this course, you will learn: Basics of matrices, such as notation, dimensions, types, and addressing entries Operations on a single matrix, including scalar multiplication, transpose, determinant, and adjoint Operations on two matrices, such as addition, subtraction, and multiplication Echelon Forms and performing elementary row operations Inverses, including invertible and singular matrices, and trig functions Gauss-Jordan elimination, determinant properties, and matrices as vectors Vector spaces, including dimensions, Euclidean spaces, closure properties, and axioms Eigenvalues and Eigenvectors, and how to locate the associated Eigenvectors and Eigenvalues Bonus: Concepts in elementary algebra With this course, you will get: Lesson Videos: Watch as the concepts are clearly and concisely taught from scratch Solved Examples: Each topic is taught with the aid of solved examples. Currently, udemy is offering the Complete Linear Algebra for Data Science & Machine Learning for up to 87 % off i.e. INR 449 (INR 3,500).

Who Can Opt for this Course?

  • Students who wish to excel in Linear Algebra and are enrolled in the course or who want to enroll
  • Professionals who require a math review, particularly in the areas of algebra and linear algebra
  • Those who desire to work with linear systems and vector spaces in math, science, and engineering
  • Anyone who wants to become proficient in linear algebra for use in computer programming, computer graphics, artificial intelligence, data analysis, machine learning, deep learning, data science, etc

Course Highlights

Key HighlightsDetails
Registration LinkApply Now!
PriceINR 449 (INR 3,50087 % off
Duration17 Hours
Student Enrollment4,294 students
InstructorKashif A.
Topics Covered
  • Dimension (Order) of a Matrix
  • The Formula: Inverse (A) = Adjoint (A) / Determinant (A)
  • Systems of Linear Equations
Course LevelN.A
Total Student Reviews688

Learning Outcomes

  • How to ace your linear algebra exam and the fundamentals of linear algebra
  • Matrices’ fundamentals (notation, dimensions, types, addressing the entries etc)
  • Operations, such as scalar multiplication, transposition, determinant, and adjoint, on a single matrix
  • Operations using two matrices, such as addition, subtraction, and matrix multiplication
  • Finding Echelon Forms and performing simple row operations (REF & RREF)
  • Inverses, such as singular and invertible matrices, as well as the Cofactor approach
  • Employing matrices and inverse matrices to solve systems of linear equations, using Cramer’s method to solve AX = B
  • The characteristics of determinants and Gauss-Jordan elimination
  • Matrices can be thought of as vectors, complete with the head-to-tail rule, components, magnitude, and midpoint
  • Dimensions, Euclidean spaces, closure conditions, and axioms for vector spaces
  • Span, linear dependence, and linear combinations with span for a vector space
  • A matrix’s subspace, null space, and matrix-vector products
  • Basis and standard basis, as well as determining if a group of provided vectors serves as the foundation of a vector space Identifying Eigenvalues and their related Eigenvectors, as well as how to do so
  • Rudimentary algebraic ideas

Course Content

S.No.Module (Duration)Topics
1.Welcome and Introduction (03 minutes)Welcome and Introduction
SOLUTIONS of Assignments
2.Basics of Matrices (32 minutes)Matrices and their Significance – 001
Matrix Notation – 002
Dimension (Order) of a Matrix – 003
Quiz 1: Dimensions of a Matrix
Addressing Elements of a Matrix – 004
Quiz 2: Addressing Elements of a Matrix
Solving Linear Systems in 2 Unknowns – 005
Quiz 3: Solving Linear Systems in 2 Unknowns
Solving Linear Systems in 3 Unknowns – 006
Quiz 4: Solving Linear Systems in 3 Unknowns
3.Basics of Matrices (Continued) (01 hour 18 minutes)IMPORTANT – This section is OPTIONAL
Types of Matrices
Addition and Subtraction of Matrices
Multiplication of Scalars with Matrices
Multiplication of two Matrices
Inverse and Determinant of a 2×2 Matrix
The Formula: Inverse (A) = Adjoint (A) / Determinant (A)
* EXAMPLE – Inverse of a 2×2 Matrix
Using Matrices to Solve Simultaneous Linear Equations
* EXAMPLE – Using Matrices to Solve Simultaneous Linear Equations
CHALLENGE QUESTION – Using Matrices to Solve Simultaneous Linear Equations
4.Matrices and Systems of Linear Equations (46 minutes)The Online Matrix Calculator: A FREE Tool
Systems of Linear Equations
Systems of Linear Equations – Continued
Elementary Row Operations
Row Echelon Form (REF)
Reduced Row Echelon Form (RREF)
* ASSIGNMENT 1: Matrices and Linear Equations
5.Matrix Algebra and Operations (21 minutes)Matrix Algebra – Addition and Subtraction
Matrix Algebra – Scalar Multiplication
Matrix Algebra – Matrix Multiplication
Transpose of a Matrix
** ASSIGNMENT 2: Matrix Algebra & Operations
6.Determinant of a Matrix (20 minutes)Determinant of a 2×2 Matrix
Determinant of a 3×3 Matrix
Finding Determinants Quickly
*** ASSIGNMENT 3: Computing Determinants
7.Inverse of a Matrix (46 minutes)Inverse exists only for Square Matrices
Singular Matrices
Importance of Inverse in solving Linear Systems
Inverse of a 2×2 Matrix
Inverse of a 3×3 Matrix – The Two Methods
Inverse of a 3×3 Matrix – The Co-factor Method
Inverse of a 3×3 Matrix – Gauss-Jordan Elimination Method
8.Properties of Determinants (14 minutes)Properties of Determinants – Row Operation 1
Properties of Determinants – Row Operation 2
Properties of Determinants – Row Operation 3
Properties of Determinants – All Row Operations
Properties of Determinants – Row Operations Applied
Properties of Determinants – Another Property
9.*** OPTIONAL: Introduction to Vectors (52 minutes)Introduction to the Section
Scalars and Vectors
Geometrical Representation of Vectors
Vector Addition and Subtraction
Laws of Vector Addition and Head to Tail Rule
Unit Vector
Components of a Vector in 2D
Position Vector
3-D Vectors and Magnitude of a Vector
Displacement Vector
Finding Midpoint using Vectors
10.Vector Spaces (40 minutes)Introduction to Vector Spaces
Euclidean Vector Spaces – Part 1
Euclidean Vector Spaces – Part 2
Euclidean Vector Spaces – Part 3
Definition and Closure Properties
Axioms of Vector Spaces
Example of Closure Properties
Example 1 of Vector Spaces
Example 2 of Vector Spaces
11.Subspace and Nullspace (24 minutes)Subspaces – Introduction
Subspaces – Example
Subspaces – Example 2
Subspaces – Example 3
Nullspace of a Matrix
Nullspace of a Matrix – Example
**** ASSIGNMENT 4: Vector Spaces, Subspaces and Null Spaces
12.Span and Spanning Sets (20 minutes)Span of a set of vectors
Span of a set of vectors – Example
Spanning Set for a Vector Space – Introduction and Examples
Spanning Set – Example 3
Spanning Set – Example 4
13.Linear Dependence and Independence (31 minutes)Linear Dependence – Introduction
Linear Dependence – Definition
Linear Dependence – Examples
Linear Dependence – More Examples
Linear Dependence – A faster method to check dependency
Linear Dependence – If X is not a Square Matrix
Linear Dependence – Example of a Non-square X Matrix
14.Basis and Dimension (17 minutes)Basis – Definition and Example
Basis – Another Example
Basis – Dimension of a Vector Space
Basis – Example of Dimension of a Vector Space
Basis – Standard Basis
***** ASSIGNMENT 5: Span, Linear Independence and Basis
15.Eigenvalues and Eigenvectors (22 minutes)Introduction to Eigenvalues and Eigenvectors
How to Calculate Eigenvalues and Eigenvectors
EXAMPLE: Calculating Eigenvalues and Eigenvectors of a 2×2 Matrix
16.Basic Algebra Concepts (Additional Lessons) (04 hours 41 minutes)Mathematical Operators and their Precedence (BODMAS)
Power and Roots
Rounding and Estimation
Rounding with Decimal Places
Rounding with Significant Figures
Fractions, Decimals and Percentages
Ratio and Proportion
Introduction to the Number System
Natural Numbers
Whole Numbers
Rational Numbers
Irrational Numbers
Real Numbers
Venn Diagram and Flowchart
The Coordinate System
The Coordinate System – continued
Length of a Line Segment
EXAMPLES: Length of a Line Segment
EXERCISE: Length of a Line Segment
EXAMPLE: Midpoint of a Line Segment
EXERCISE: Midpoint of a Line Segment
Equation of a Straight Line
Gradient of a Straight Line
EXAMPLE 1: Equation of a Straight Line
EXAMPLE 2: Equation of a Straight Line
EXAMPLE 3: Equation of a Straight Line
EXERCISES: Equation of a Straight Line
Other Forms of Linear Equations
A Second Formula for a Straight Line
Straight Lines
Intersection of Two Lines
EXAMPLE: Intersection of Two Lines
EXERCISE: Intersection of Two Lines
ACTIVITY 1: Straight Lines
ACTIVITY 2: Straight Lines
Parallel and Perpendicular Lines
EXAMPLES: Parallel and Perpendicular Lines
EXERCISES: Parallel and Perpendicular Lines
Udemy Supplement LA
Graphs of Common Functions
Straight Line
Graph of a Linear Function
Validation of Graphs as Functions
Library of Functions
ACTIVITY: Memorize these Graphs
Translations – Vertical Shift
Translations – Horizontal Shift
ACTIVITY: Translations
SUMMARY – Translations
EXERCISE: Translations
Transformations – Stretching and Compression
ACTIVITY: Transformations
EXERCISE: Transformations
SUMMARY: Stretching and Compression
SUMMARY: Translation and Transformation
Reflection about X-axis and Y-axis
SUMMARY: Reflections
EXERCISE: Sketching Complex Graphs
Common Graphs
Basic Types of Graph Manipulations-1
Basic Types of Graph Manipulations-2
EXAMPLE: Manipulation of Graphs
17.Congratulations and Bonus Material (05 hours 18 minutes)Congratulations and Thank You!
Bonus Material: Getting free Trial of Software to create Whiteboard Animations
Overview of the Project Screen
Customizing the Default Settings
Creating a New Project
Brief Overview of the Tools and Saving the Project
Changing the Default Drawing Hand
Canvas Color and Texture
Adding the First Image and Adjusting it
Image Properties
Adding Text
Exporting Your Video (and more Text Properties)
Project 1 – Solution, and Adding Background Music
Solution and adding Tracks – P1soln – WBA
Camera Settings
More Camera Settings and Creating a New Scene
Timeline and Relocating Copied Elements
Drawing Without Hand Leaving the Screen, and Native Elements
Move In Effect
Project 2 – Solution Part 1
Project 2 – Solution Part 2
Charts and their Types
Importing Charts from Microsoft Excel etc.
The Erase Effect
Graphic Enhancements and Filter Effects
Project 3 – Solution
GIF Files in VideoScribe
Making your own GIF files and Importing to VideoScribe
Drawing Bitmap and JPEG Images in VideoScribe
Writing Text in Languages Not Supported by VideoScribe
The Morph Effect
Handbrake Software to Compress Exported Videos Without Losing Quality
Project 4 – Solution Part 1
Project 4 – Solution Part 2
Project 5 – Solution and Recording Voice Over
BONUS Lecture: Get Any of Kashif’s Courses for Up to 95% Off
Royalty Free Resources

Resources Required

  • A deep desire to understand vectors and matrices Possess the ability to manipulate integers and fractions using basic mathematical operations (+, -, x, )
  • Understanding of how to calculate a linear equation, like as 3x-4=11
  • Understanding of fundamental algebraic principles, such as powers and roots, factoring, simplifying fractions, solving equations, and graphing
  • To take this course, you only need to be familiar with basic math and algebra
  • The majority of the aforementioned prerequisite subjects are covered in the course, which is the finest part

Featured Review

Amy Bourque (5/5) : I use this class to supplement the very quick linear algebra section in a data science bootcamp. It was the perfect accompaniment to help me understand linear algebra in order to visualize and comprehend how it applies to data science.


  • John Ross (5/5) : Everything is very well explained and going at an excellent speed for a beginner.
  • Kuro Saki (5/5) : Amazing course for anybody who want to get into data science and AI since Linear Algebra is very important for that.
  • Sharon Moak (5/5) : So far the pacing is perfect and the explanations are thorough.
  • Om Khatri (5/5) : This is by far the best course linear algebra course out there!


  • Eliakin (2/5) : – The course is not really intended for individuals who want to “master Linear Algebra for Data Science, Data Analysis, Artificial Intelligence, Machine Learning, Deep Learning, Computer Graphics, Programming, etc.” as advertised.
  • Eliakin (2/5) : I am disappointed at 1) all the reviewers who made it seem like this course was an outstanding investment and 2) at the false advertisement.

About the Author

The instructor of this course is Kashif A. who is a Bestselling Instructor. With 4.5 Instructor Rating and 5,588 Reviews on Udemy, he/she offers 13 Courses and has taught 81,265 Students so far.

  • Kashif graduated with a Master in Engineering from one of the best US universities With 11 years of experience instructing at the collegiate level, he enjoys teaching
  • He is keen about online education and digital entrepreneurship in addition to traditional academics
  • Motion graphics and photo and video editing are areas of interest for him
  • Kashif enjoys travelling, cooking, and reading in his free time

Comparison Table

ParametersComplete Linear Algebra for Data Science & Machine LearningComplete linear algebra: theory and implementation in codeMathematical Foundations of Machine Learning
OffersINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% off
Duration18 hours34 hours16.5 hours
Rating4.9 /54.9 /54.6 /5
Student Enrollments4,29427,847102,492
InstructorsKashif A.Mike X CohenDr Jon Krohn
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