About this Course

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Learner Career Outcomes

33%

started a new career after completing these courses

12%

got a tangible career benefit from this course

12%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
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Start instantly and learn at your own schedule.
Flexible deadlines
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Advanced Level
Approx. 38 hours to complete
English

Skills you will gain

InferenceGibbs SamplingMarkov Chain Monte Carlo (MCMC)Belief Propagation

Learner Career Outcomes

33%

started a new career after completing these courses

12%

got a tangible career benefit from this course

12%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 38 hours to complete
English

Instructor

Offered by

Placeholder

Stanford University

Syllabus - What you will learn from this course

Week
1

Week 1

25 minutes to complete

Inference Overview

25 minutes to complete
2 videos (Total 25 min)
2 videos
Overview: MAP Inference9m
1 hour to complete

Variable Elimination

1 hour to complete
4 videos (Total 56 min)
4 videos
Complexity of Variable Elimination12m
Graph-Based Perspective on Variable Elimination15m
Finding Elimination Orderings11m
1 practice exercise
Variable Elimination30m
Week
2

Week 2

18 hours to complete

Belief Propagation Algorithms

18 hours to complete
9 videos (Total 150 min)
9 videos
Properties of Cluster Graphs15m
Properties of Belief Propagation9m
Clique Tree Algorithm - Correctness18m
Clique Tree Algorithm - Computation16m
Clique Trees and Independence15m
Clique Trees and VE16m
BP In Practice15m
Loopy BP and Message Decoding21m
2 practice exercises
Message Passing in Cluster Graphs30m
Clique Tree Algorithm30m
Week
3

Week 3

2 hours to complete

MAP Algorithms

2 hours to complete
5 videos (Total 74 min)
5 videos
Finding a MAP Assignment3m
Tractable MAP Problems15m
Dual Decomposition - Intuition17m
Dual Decomposition - Algorithm16m
1 practice exercise
MAP Message Passing30m
Week
4

Week 4

15 hours to complete

Sampling Methods

15 hours to complete
5 videos (Total 100 min)
5 videos
Markov Chain Monte Carlo14m
Using a Markov Chain15m
Gibbs Sampling19m
Metropolis Hastings Algorithm27m
2 practice exercises
Sampling Methods30m
Sampling Methods PA Quiz30m
1 hour to complete

Inference in Temporal Models

1 hour to complete
1 video (Total 20 min)
1 practice exercise
Inference in Temporal Models30m

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About the Probabilistic Graphical Models Specialization

Probabilistic Graphical Models

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