## このコースについて

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100%オンライン

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### 提供： ## 修士号の取得を目指しましょう

この コース は ロシア国立研究大学経済高等学院（National Research University Higher School of Economics） の100%オンラインの Master of Data Science の一部です。 プログラムのすべてで認定されれば、それらのコースが学位学習に加算されます。

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3時間で修了

## Conditional probability and Independence

3時間で修了
13件のビデオ （合計123分）
13件のビデオ
Conditional probability. Motivation and Example13 分
Conditional probability. Definition8 分
Independent events. Example7 分
Independent events. Definition12 分
Mosaic Plot. Visualization of conditional probabilities and Independence11 分
Using independence to find probabilities. Examples10 分
Pairwise and mutual independence12 分
Bernoulli Scheme11 分
Law of total probability14 分
Bayes's rule4 分
Python for conditional probabilities9 分
Conditional probability. Highlights3 分
7の練習問題
Coins, dices and conditional probability20 分
Independence and intersection5 分
Fair coin and independence6 分
Mutual independence conditions5 分
Call center total probability5 分
Bayes's taxi companies5 分
2

3時間で修了

## Random variables

3時間で修了
15件のビデオ （合計150分）
15件のビデオ
Examples of random variables11 分
Mathematical definition of random variable5 分
Probability distribution and probability mass function (PMF)15 分
Binomial distribution10 分
Expected value of random variable. Motivation and definition14 分
Expected value example and calculation11 分
Expected value as best prediction15 分
Variance of random variable. Motivation and definition7 分
Discrete random variables with infinite number of values11 分
Saint Petersburg Paradox. Example of infinite expected value6 分
Geometric and Poisson distributions6 分
Generating discrete random variables with Python11 分
Numpy, scipy and matplotlib for generation and visualization of common distributions12 分
Random variables. Highlights3 分
3の練習問題
Expected value exercises20 分
Variance skill test25 分
Random variables and geometric series10 分
3

3時間で修了

## Systems of random variables; properties of expectation and variance, covariance and correlation.

3時間で修了
16件のビデオ （合計127分）
16件のビデオ
Linear transformations of random variables8 分
Linearity of expected value6 分
Symmetric distributions and their expected values6 分
Functions of random variables5 分
Properties of variance6 分
Sum of random variables. Expected value and variance8 分
Joint probability distribution12 分
Marginal distribution8 分
Independent random variables7 分
Another example of non-independent random variables8 分
Expected value of product of independent random variables8 分
Variance of sum of random variables. Covariance11 分
Properties of covariance10 分
Correlation of two random variables7 分
Systems of random variables. Highlights3 分
7の練習問題
PMF of linear transformations5 分
Expectation properties5 分
Joint distribution skill test15 分
Joint PMF10 分
Variance of Binomial random variable5 分
Covariance for a dice roll5 分
Correlation quiz5 分
4

3時間で修了

## Continuous random variables

3時間で修了
16件のビデオ （合計156分）
16件のビデオ
Continuous random variables. Motivation and Example10 分
Probability density function (PDF)9 分
Cumulative distribution function (CDF)13 分
Properties of CDF6 分
Examples of probability density functions10 分
Histogram as approximation to a graph of PDF11 分
Expected value of continuous random variable9 分
Variance of continuous random variable. Properties of expected value and variance7 分
Transformations of continuous random variables and their PDFs11 分
Joint CDF and PDF. Level charts. Marginal PDF10 分
Independence, covariance and correlation of continuous random variables9 分
Mixed random variables. Example11 分
Generating and visualizing continuous random variables with Python10 分
Generating correlated random variables with Python11 分
8の練習問題
CDF of discrete random variable7 分
PDF and CDF skill test15 分
Finding expectation with PDF5 分
Finding variance with PDF5 分
Expectation of a function of random variable2 分
PDF skill test7 分
Variance of sum of Gaussian random variables5 分
Distinguishing random variables3 分

## Mathematics for Data Science専門講座について

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.... ## よくある質問

• Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

• The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

• The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.