Description
Complete Linear Algebra for Data Science is the name of the visual training collection in the field of software engineering and linear algebra. In fact, in this training course, you will get to know the concept of linear algebra in a very comprehensive and complete way for use in data science and machine learning. All the materials and trainings of this course have been presented to the students in the simplest possible way. Having various tests at the end of the sessions helps students to improve their skills fundamentally.
Also, in making this training course, it is assumed that you students have no previous knowledge and experience. Therefore, all the content will be taught to you step by step. The approach of this course can also help you in realistic and practical learning by doing real exercises. This course will be very suitable for developers of data, artificial intelligence, machine learning, deep learning, computer graphics, programming, etc.
Items taught in this course:
- Learning and getting to know the basics of linear algebra
- Familiarity with the concept and basics of the matrix and its use in projects
- Learning to perform operations on a single matrix such as scaling
- Getting to know how to operate on two matrices, such as matrix multiplication
- Learning how to solve a system of linear equations using matrices and inverse matrices
- And…
Details of Complete Linear Algebra for Data Science course
- English language
- Duration: 17:53:59
- Number of courses: 210
- Lecturer: Kashif A.
- File format: mp4
Course headings for Complete Linear Algebra for Data Science
Course content
210 lectures 17:53:59
Welcome and Introduction
1 lecture 02:43
Basics of Matrices
6 lectures 32:28
Basics of Matrices (Continued)
12 lectures 01:18:49
Matrices and Systems of Linear Equations
7 lectures 46:36
Matrix Algebra and Operations
5 lectures 21:24
Determinant of a Matrix
4 lectures 20:43
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 Nullspace
7 lectures 24:25
Span and Spanning Sets
5 lectures 20:02
Linear Dependence and Independence
7 lectures 31:54
Basis and Dimension
6 lectures 17:54
Eigenvalues and Eigenvectors
3 lectures 22:20
Basic Algebra Concepts (Additional Lessons)
78 lectures 04:41:52
Congratulations and bonus material
36 lectures 05:18:44
Course prerequisites
- A passion to learn about Matrices and Vectors
- Ability to perform basic mathematical operations (+, -, x, ÷) on numbers and fractions
- Knowledge of how to solve a linear equation (eg find x in 3x-4=11)
- Understanding of basic Algebra concepts, eg Powers and Roots, simplifying Fractions, Factorization, solving Equations and drawing Graphs.
- You only need to know basic Math and Algebra to take this course.
- And the best thing is, most of the above prerequisite topics are covered inside the course
Pictures
Sample video of Complete Linear Algebra for Data Science
Installation guide
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download link
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Size
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