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.
Foundations of Data Science
Course Features
Mathematics for data science practitioners
Primer on elementary algebra
Linear algebra
Calculus
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.
