About this Course

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Flexible deadlines
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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Intermediate Level

Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.

Approx. 48 hours to complete
English

What you will learn

  • Explain why probability is important to statistics and data science.

  • See the relationship between conditional and independent events in a statistical experiment.

  • Calculate the expectation and variance of several random variables and develop some intuition.

Skills you will gain

Probabilitycentral limit theoremcontinuous random variablesBayes' Theoremdiscrete random variables
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.

Approx. 48 hours to complete
English

Offered by

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University of Colorado Boulder

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Data Science from University of Colorado Boulder. 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

9 hours to complete

Descriptive Statistics and the Axioms of Probability

9 hours to complete
3 videos (Total 51 min), 3 readings, 3 quizzes
Week
2

Week 2

7 hours to complete

Conditional Probability

7 hours to complete
2 videos (Total 52 min), 1 reading, 3 quizzes
Week
3

Week 3

8 hours to complete

Discrete Random Variables

8 hours to complete
4 videos (Total 78 min), 1 reading, 3 quizzes
Week
4

Week 4

9 hours to complete

Continuous Random Variables

9 hours to complete
4 videos (Total 97 min), 2 readings, 3 quizzes

About the Statistical Inference for Data Science Applications Specialization

Statistical Inference for Data Science Applications

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