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MATH - Linear Algebra I - Acalog ACMS™

What will I learn? How will I learn? How will I be assessed? What happens if I fail? Compensation This module is not passable by compensation Resit Opportunities End of Semester Exam Remediation If you fail this module you may repeat, resit or substitute where permissible. Am I eligible to take this module? Curricular information is subject to change. If you fail this module you may repeat, resit or substitute where permissible. Flexible deadlines. Flexible deadlines Reset deadlines in accordance to your schedule.

Beginner Level.

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Hours to complete. Available languages.

Course level

English Subtitles: English. Chevron Left. Syllabus - What you will learn from this course. Video 5 videos. Introduction: Solving data science challenges with mathematics 2m. Motivations for linear algebra 3m. Getting a handle on vectors 9m. Operations with vectors 11m. Summary 1m. Reading 4 readings. How to be successful in this course 5m. Grading policy 5m. Quiz 3 practice exercises. Exploring parameter space 20m.


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Solving some simultaneous equations 15m. Doing some vector operations 14m. Video 8 videos. Introduction to module 2 - Vectors 49s.

Course Descriptions

Projection 6m. Changing basis 11m.

Basis, vector space, and linear independence 4m. Applications of changing basis 3m. Quiz 4 practice exercises. Dot product of vectors 15m. Changing basis 15m. Linear dependency of a set of vectors 15m. Vector operations assessment 15m. Matrices, vectors, and solving simultaneous equation problems 5m. How matrices transform space 5m. Types of matrix transformation 8m. Composition or combination of matrix transformations 8m.

Solving the apples and bananas problem: Gaussian elimination 8m. Going from Gaussian elimination to finding the inverse matrix 8m. Determinants and inverses 10m. Summary 59s. Quiz 2 practice exercises. Using matrices to make transformations 12m. Solving linear equations using the inverse matrix 16m. Video 6 videos. Introduction: Einstein summation convention and the symmetry of the dot product 9m. Matrices changing basis 11m. Doing a transformation in a changed basis 4m.

Orthogonal matrices 6m. The Gram—Schmidt process 6m.

Example: Reflecting in a plane 14m. Non-square matrix multiplication 20m.


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Example: Using non-square matrices to do a projection 12m. Show More. Video 9 videos. Welcome to module 5 52s. What are eigenvalues and eigenvectors? Special eigen-cases 3m. Calculating eigenvectors 10m. Changing to the eigenbasis 5m. Eigenbasis example 7m. Introduction to PageRank 8m. Wrap up of this linear algebra course 1m. Reading 1 reading.

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