About this Course

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Shareable Certificate
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Intermediate Level

Familiarity with calculus-based probability, the principles of maximum likelihood estimation, and Bayesian inference.

Approx. 22 hours to complete
English

Skills you will gain

  • Bayesian Statistics
  • Forecasting
  • Dynamic Linear Modeling
  • Time Series
  • R Programming
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

Familiarity with calculus-based probability, the principles of maximum likelihood estimation, and Bayesian inference.

Approx. 22 hours to complete
English

Offered by

Placeholder

University of California, Santa Cruz

Syllabus - What you will learn from this course

Week
1

Week 1

6 hours to complete

Week 1: Introduction to time series and the AR(1) process

6 hours to complete
9 videos (Total 94 min), 12 readings, 5 quizzes
Week
2

Week 2

5 hours to complete

Week 2: The AR(p) process

5 hours to complete
9 videos (Total 96 min), 8 readings, 3 quizzes
Week
3

Week 3

5 hours to complete

Week 3: Normal dynamic linear models, Part I

5 hours to complete
10 videos (Total 114 min), 7 readings, 3 quizzes
Week
4

Week 4

4 hours to complete

Week 4: Normal dynamic linear models, Part II

4 hours to complete
7 videos (Total 103 min), 4 readings, 3 quizzes

About the Bayesian Statistics Specialization

Bayesian Statistics

Frequently Asked Questions

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