About this Course

43,772 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

Some background in Python programming language and algebra.

Approx. 14 hours to complete
English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

Some background in Python programming language and algebra.

Approx. 14 hours to complete
English

Offered by

Placeholder

National Research University Higher School of Economics

Start working towards your Master's degree

This course is part of the 100% online Master of Data Science from National Research University Higher School of Economics. If you are admitted to the full program, your courses count towards your degree learning.

Syllabus - What you will learn from this course

Week
1

Week 1

5 hours to complete

Systems of linear equations and linear classifier

5 hours to complete
15 videos (Total 118 min), 2 readings, 2 quizzes
15 videos
Introduction to Linear Algebra42s
Linear Algebra and Calculus4m
Matrices and Multidimensional Vectors10m
Matrix arithmetics6m
Properties of matrix operations and some special matrices10m
Vectors and matrices in Python4m
Systems of linear equations11m
Matrix inverse13m
Gaussian elimination. The first example4m
Elementary row operations6m
Gaussian elimination. Main theorem.5m
Gaussian Elimination. The algorithm.13m
The Inverse matrix with Gaussian elimination5m
LU and PLU decomposition17m
2 readings
About the University10m
Covered Python methods20m
1 practice exercise
Week 11h
Week
2

Week 2

2 hours to complete

Full rank decomposition and systems of linear equations

2 hours to complete
14 videos (Total 86 min)
14 videos
Abstract algebra and linear algebra11m
Axioms of vector spaces: first application6m
Examples of vector spaces8m
Subspaces1m
Linear combinations and spans2m
Basis and linear dependence7m
Dimension of a vector space5m
Examples of bases7m
Linear dependence and rank3m
Formula for the solution of a SLAE9m
An example of vector representation of the set of solutions7m
Rouché–Capelli Theorem4m
Full rank decomposition8m
1 practice exercise
Week 230m
Week
3

Week 3

2 hours to complete

Euclidean spaces

2 hours to complete
10 videos (Total 85 min)
10 videos
Coordinates change example9m
Euclidean space8m
Geometry and Euclidean spaces1m
Orthogonal and orthonormal bases4m
Distance and orthogonal projections6m
Inconsistent systems and the least squares method12m
Linear regression example8m
Introduction to support vector machine16m
Linear regression and SVM with Python4m
1 practice exercise
Week 330m
Week
4

Week 4

4 hours to complete

Final Project

4 hours to complete
1 video (Total 2 min), 1 reading, 2 quizzes
1 reading
References and further reading10m
1 practice exercise
Life expectancy prediction quiz1h

Reviews

TOP REVIEWS FROM FIRST STEPS IN LINEAR ALGEBRA FOR MACHINE LEARNING

View all reviews

About the Mathematics for Data Science Specialization

Mathematics for Data Science

Frequently Asked Questions

More questions? Visit the Learner Help Center.