- Instructor: Mahad Salad
- Lectures: 44
- Students: 5
- Duration: 30 days
In this course, we will explain the essentials of Linear Algebra and everything that you need to understand the basics of linear algebra. The course is very hands on, with lots of examples and practice problems.
If you want to begin a modern courses in Machine Learning, Data Science, Computer Science, Electrical Engineering and Physics you will encounter some mathematic concepts, like matrices, for example in analytical mechanics or relativistic quantum mechanics we have matrices and we use Einstein summation convention, if you don’t know this convention it would be impossible for you to start these courses so, this course of matrices is intended for any students wishing to pursue these degrees as Linear Algebra is the prerequisite for these courses.
This course contains a series of 45 videos explained in Somali language that are also broken up into various levels. Each video builds upon the previous one.
Using the Content you can pick and choose the topics that are causing you the most difficulty and find the videos easily in numerical order.
This course of Linear Algebra there are also many standard example questions so you can practice what you have learned and a step by step solution procedure which will teach you strategies to tackle various types of problems.
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Overview
In this section we'll show you how this course has been structured and how to get the most out of it through content. We'll also show you first free video in order to look in our course
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Matrices part1
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Lecture 2.11B Definition of Matrices33m
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Lecture 2.21C Definition of Matrices28m
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Lecture 2.31D Definition of Matrices24m
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Lecture 2.41E Definition of Matrices23m
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Lecture 2.52A Determinant of Matrices31m
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Lecture 2.62B Determinant of Matrices32m
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Lecture 2.73A Inverse Matrices31m
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Lecture 2.83B Inverse Matrices30m
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Lecture 2.93C Inverse Matrices30m
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Lecture 2.103D Inverse Matrices27m
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Matrices part2
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Lecture 3.13E Inverse Matrices28m
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Lecture 3.23F Inverse Matrices30m
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Lecture 3.33G Inverse Matrices31m
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Lecture 3.44A Solving Leaner Equation by using Inverse Matrices24m
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Lecture 3.54B Solving Leaner Equation by using Inverse Matrices30m
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Lecture 3.64C Solving Leaner Equation by using Inverse Matrices30m
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Lecture 3.75A Cramer’s Rule Matrices19m
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Lecture 3.85B Cramer’s Rule Matrices30m
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Lecture 3.96A Matrices31m
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Lecture 3.106B Matrices32m
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Matrices part 3
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Lecture 4.17A Consistent Matrix25m
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Lecture 4.27B Consistent Matrix22m
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Lecture 4.38A Inconsistent Matrix22m
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Lecture 4.49A Area of a Triangle Using Matrix20m
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Lecture 4.59B Collinearity23m
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Lecture 4.69C Collinearity20m
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Lecture 4.710A Sequences and Series31m
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Lecture 4.810B Sequences and Series32m
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Lecture 4.910C Sequences and Series31m
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Lecture 4.1010D Sequences and Series29m
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Matrices part 4
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Lecture 5.110E Sequences and Series31m
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Lecture 5.210F Sequences and Series31m
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Lecture 5.311A Arithmetic Sequence and Series26m
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Lecture 5.411B Arithmetic Sequence and Series30m
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Lecture 5.511C Arithmetic Sequence and Series28m
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Lecture 5.611D Arithmetic Sequence and Series24m
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Lecture 5.711E Arithmetic Sequence and Series26m
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Lecture 5.811F Arithmetic Sequence and Series25m
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Lecture 5.912A Geometric Sequence and Series30m
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Lecture 5.1012C Geometric Sequence and Series33m
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Lecture 5.1112D Geometric Sequence and Series27m
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Lecture 5.1212E Geometric Sequence and Series22m
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