About this Course

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Learner Career Outcomes

38%

started a new career after completing these courses

24%

got a tangible career benefit from this course
Flexible deadlines
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Shareable Certificate
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Advanced Level

Course requires strong background in calculus, linear algebra, probability theory and machine learning.

Approx. 33 hours to complete
English

Skills you will gain

Bayesian OptimizationGaussian ProcessMarkov Chain Monte Carlo (MCMC)Variational Bayesian Methods

Learner Career Outcomes

38%

started a new career after completing these courses

24%

got a tangible career benefit from this course
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.
Advanced Level

Course requires strong background in calculus, linear algebra, probability theory and machine learning.

Approx. 33 hours to complete
English

Offered by

Placeholder

HSE University

Syllabus - What you will learn from this course

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Week
1

Week 1

3 hours to complete

Introduction to Bayesian methods & Conjugate priors

3 hours to complete
10 videos (Total 57 min), 3 readings, 2 quizzes
Week
2

Week 2

7 hours to complete

Expectation-Maximization algorithm

7 hours to complete
17 videos (Total 168 min)
Week
3

Week 3

2 hours to complete

Variational Inference & Latent Dirichlet Allocation

2 hours to complete
11 videos (Total 98 min)
Week
4

Week 4

6 hours to complete

Markov chain Monte Carlo

6 hours to complete
11 videos (Total 122 min)

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About the Advanced Machine Learning Specialization

Advanced Machine Learning

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