“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 Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 449 ( |
| Duration | 17 Hours |
| Rating | 4.9/5 |
| Student Enrollment | 4,294 students |
| Instructor | Kashif A. https://www.linkedin.com/in/kashifa. |
| Topics Covered |
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| Course Level | N.A |
| Total Student Reviews | 688 |
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 | ||
| SUMMARY | ||
| 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 | ||
| Estimating | ||
| Fractions, Decimals and Percentages | ||
| Ratio and Proportion | ||
| Introduction to the Number System | ||
| Natural Numbers | ||
| Whole Numbers | ||
| Integers | ||
| Rational Numbers | ||
| Irrational Numbers | ||
| EXERCISES | ||
| Real Numbers | ||
| Venn Diagram and Flowchart | ||
| EXAMPLES 1 | ||
| EXAMPLES 2 | ||
| EXAMPLE 3 | ||
| COORDINATE GEOMETRY & STRAIGHT LINES | ||
| 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 | ||
| SUMMARY | ||
| 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 | ||
| EXERCISE | ||
| SUMMARY | ||
| 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 | ||
| SUMMARY | ||
| Udemy Supplement LA | ||
| FUNCTIONS, GRAPHS & TRANSFORMATIONS | ||
| Functions | ||
| Graphs of Common Functions | ||
| Straight Line | ||
| Graph of a Linear Function | ||
| Validation of Graphs as Functions | ||
| Library of Functions | ||
| Asymptotes | ||
| Limits | ||
| 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 | ||
| SUMMARY | ||
| 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.
Pros
- 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!
Cons
- 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
| Parameters | Complete Linear Algebra for Data Science & Machine Learning | Complete linear algebra: theory and implementation in code | Mathematical Foundations of Machine Learning |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 18 hours | 34 hours | 16.5 hours |
| Rating | 4.9 /5 | 4.9 /5 | 4.6 /5 |
| Student Enrollments | 4,294 | 27,847 | 102,492 |
| Instructors | Kashif A. | Mike X Cohen | Dr Jon Krohn |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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