Über diesen Kurs

33,584 kürzliche Aufrufe
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“

Some background in Python programming language and algebra.

Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“

Some background in Python programming language and algebra.

Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch

von

National Research University Higher School of Economics-Logo

National Research University Higher School of Economics

Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.

Dieses Kurs ist Teil des reinen Onlineabschlusses Master of Data Science von National Research University Higher School of Economics. Wenn Sie in das komplette Programm aufgenommen werden, werden Ihre Kurse auf Ihren Abschluss angerechnet.

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1

Woche 1

5 Stunden zum Abschließen

Systems of linear equations and linear classifier

5 Stunden zum Abschließen
15 Videos (Gesamt 118 min), 2 Lektüren, 2 Quiz
15 Videos
Introduction to Linear Algebra42
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 Lektüren
About the University10m
Covered Python methods20m
1 praktische Übung
Week 11h
Woche
2

Woche 2

2 Stunden zum Abschließen

Full rank decomposition and systems of linear equations

2 Stunden zum Abschließen
14 Videos (Gesamt 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 praktische Übung
Week 230m
Woche
3

Woche 3

2 Stunden zum Abschließen

Euclidean spaces

2 Stunden zum Abschließen
10 Videos (Gesamt 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 praktische Übung
Week 330m
Woche
4

Woche 4

4 Stunden zum Abschließen

Final Project

4 Stunden zum Abschließen
1 Video (Gesamt 2 min), 1 Lektüre, 2 Quiz
1 Lektüre
References and further reading10m
1 praktische Übung
Life expectancy prediction quiz1h

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Über den Spezialisierung Mathematics for Data Science

Behind numerous standard models and constructions in Data Science there is mathematics that makes things work. It is important to understand it to be successful in Data Science. In this specialisation we will cover wide range of mathematical tools and see how they arise in Data Science. We will cover such crucial fields as Discrete Mathematics, Calculus, Linear Algebra and Probability. To make your experience more practical we accompany mathematics with examples and problems arising in Data Science and show how to solve them in Python....
Mathematics for Data Science

Häufig gestellte Fragen

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  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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