Datalabcc: Foundations of Data Science. Data science relies on several important aspects of mathematics. In this course, you'll learn what forms of mathematics are most useful for data science, and see some worked examples of how math can solve important data science problems.

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Foundations of Data Science

Course Features

Mathematics for data science practitioners

Primer on elementary algebra

Linear algebra

Caluculus

Basic of Probability

Statistics

Lessons of this Course

1

1

Duration:

2:53

Speaker:

Introduction to the Mathematics chapter of Datalabcc's "Foundations in Data Science" series.

4

4

Duration:

5:24

Speaker:

Primer on systems of linear equations

9

9

Duration:

7:57

Speaker:

The probability of a hypothesis, given data.

11

11

Duration:

4:01

Speaker:

Why statistics are useful for data science.

12

12

Duration:

2:23

Speaker:

Statistics is exploring data.

15

15

Duration:

10:16

Speaker:

Simple description of statistical data.

16

16

Duration:

4:28

Speaker:

Inferring results from incomplete data

17

17

Duration:

06:04

Speaker:

Basics of hypothesis testing.

18

18

Duration:

08:04

Speaker:

Finding parameter values, confidence intervals.

20

20

Duration:

3:30

Speaker:

Measuring the correspondece between data and model.

22

22

Duration:

5:58

Speaker:

Common problems in statistical modelling.

23

23

Duration:

3:50

Speaker:

Common problems in statistical modelling.

24

24

Duration:

3:18

Speaker:

You don't have to be a wizard to do statistics!

25

25

Duration:

1:43

Speaker:

Overview of possible follow up courses and subjects from the same publisher.