About this Course

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Learner Career Outcomes

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Shareable Certificate
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Flexible deadlines
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Advanced Level
Approx. 67 hours to complete
English

Skills you will gain

Bayesian NetworkGraphical ModelMarkov Random Field

Learner Career Outcomes

23%

started a new career after completing these courses

22%

got a tangible career benefit from this course

11%

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. 67 hours to complete
English

Instructor

Offered by

Placeholder

Stanford University

Syllabus - What you will learn from this course

Content RatingThumbs Up84%(3,634 ratings)Info
Week
1

Week 1

1 hour to complete

Introduction and Overview

1 hour to complete
4 videos (Total 35 min)
4 videos
Overview and Motivation19m
Distributions4m
Factors6m
1 practice exercise
Basic Definitions30m
12 hours to complete

Bayesian Network (Directed Models)

12 hours to complete
15 videos (Total 190 min), 6 readings, 4 quizzes
15 videos
Reasoning Patterns9m
Flow of Probabilistic Influence14m
Conditional Independence12m
Independencies in Bayesian Networks18m
Naive Bayes9m
Application - Medical Diagnosis9m
Knowledge Engineering Example - SAMIAM14m
Basic Operations 13m
Moving Data Around 16m
Computing On Data 13m
Plotting Data 9m
Control Statements: for, while, if statements 12m
Vectorization 13m
Working on and Submitting Programming Exercises 3m
6 readings
Setting Up Your Programming Assignment Environment10m
Installing Octave/MATLAB on Windows10m
Installing Octave/MATLAB on Mac OS X (10.10 Yosemite and 10.9 Mavericks)10m
Installing Octave/MATLAB on Mac OS X (10.8 Mountain Lion and Earlier)10m
Installing Octave/MATLAB on GNU/Linux10m
More Octave/MATLAB resources10m
3 practice exercises
Bayesian Network Fundamentals30m
Bayesian Network Independencies30m
Octave/Matlab installation30m
Week
2

Week 2

2 hours to complete

Template Models for Bayesian Networks

2 hours to complete
4 videos (Total 66 min)
4 videos
Temporal Models - DBNs23m
Temporal Models - HMMs12m
Plate Models20m
1 practice exercise
Template Models30m
12 hours to complete

Structured CPDs for Bayesian Networks

12 hours to complete
4 videos (Total 49 min)
4 videos
Tree-Structured CPDs14m
Independence of Causal Influence13m
Continuous Variables13m
2 practice exercises
Structured CPDs30m
BNs for Genetic Inheritance PA Quiz30m
Week
3

Week 3

18 hours to complete

Markov Networks (Undirected Models)

18 hours to complete
7 videos (Total 106 min)
7 videos
General Gibbs Distribution15m
Conditional Random Fields22m
Independencies in Markov Networks4m
I-maps and perfect maps20m
Log-Linear Models22m
Shared Features in Log-Linear Models8m
2 practice exercises
Markov Networks30m
Independencies Revisited30m
Week
4

Week 4

22 hours to complete

Decision Making

22 hours to complete
3 videos (Total 61 min)
3 videos
Utility Functions18m
Value of Perfect Information17m
2 practice exercises
Decision Theory30m
Decision Making PA Quiz30m

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About the Probabilistic Graphical Models Specialization

Probabilistic Graphical Models

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