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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Probabilistic Graphical Models (PGMs) is considered to be a strong foundation for encrypting probability arrangement over composite domains. Hence, Probabilistic Graphical Models 2: Inference is drafted to address the questions related to probabilistic inference. This course depends upon the concepts from graph algorithms, probability theory, and machine learning. These concepts are the base for the advanced methods used in various applications like speech recognition, medical diagnosis, natural language processing, etc. These advanced methods are also essential tools in composing various machine learning problems.
In an order of three, Probabilistic Graphical Models 2: Inference is the second one. While the first course, focused on description, this course would address the question occurs in probabilistic inference or in other words use of PGM in answering the questions. PGM is described as a very high dimensional diffusion but its framework is drafted in such a way that it can answer the questions efficiently. The course introduces both approximate and accurate algorithms for the variety of inference tasks, and also talks over the application of each algorithm.
The Highlights
- Offered by Stanford
- Completely designed in an online way
- 38 hours approximate course duration
- Available in different languages
- Certification from Coursera
Programme Offerings
- online
- Programming graded assignments
- Course Reading
- practice quizzes
- Pre-recorded Modules
- Graded Exams
- Self-paced learning.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | StanfordCoursera |
Probabilistic Graphical Models -2 programme fees details
Head | Amount in INR |
Probabilistic Graphical Models 2: Inference (audit only) | Free |
| Probabilistic Graphical Models 2: Inference - 1 month | Rs. 4,115/- |
| Probabilistic Graphical Models 2: Inference - 3 months | Rs. 12,345/- |
| Probabilistic Graphical Models 2: Inference - 6 months | Rs. 24,690/- |
Eligibility Criteria
Certification Qualifying Details
A certificate of completion is provided by Coursera to only those candidates that complete the programme and also make fee payment for the course.
What you will learn
- After completing the course, the candidates would learn to execute the fundamental steps of a message transmitting algorithm or variable elimination.
- The candidates would know about the types of inference experience in graphical models, MAP inference, and conditional probability queries.
- The candidates will learn to create Metropolis-Hastings project distributions that give accurate and satisfying results.
Who it is for
Admission Details
Candidates willing to enrol for Probabilistic Graphical Models 2: Inference programme, need to follow the steps that are given below:
Step 1: Visit the course page. https://www.coursera.org/learn/probabilistic-graphical-models-2-inference
Step 2: Then a window will appear for sign up. So, candidates need to create a login id via Facebook or Google.
Step 3: This will give access to 7-days to the candidates for a free trial.
Step 4: At the end of the trial period, candidates need to make a fee payment on a monthly basis to continue learning.
Step 5: Coursera accepts online payment and hence candidates can easily transfer the payments online.
The Syllabus
Videos
- Overview: Conditional Probability Queries
- Overview: MAP Inference
Videos
- Variable Elimination Algorithm
- complexity of Variable Elimination
- Graph-Based Perspective on Variable Elimination
- Finding Elimination Orderings
Quiz
- Variable Elimination
Videos
- Belief Propagation Algorithm
- Properties of Cluster Graphs
- Properties of Belief Propagation
- Clique Tree Algorithm - Correctness
- Clique Tree Algorithm - Computation
- Clique Trees and Independence
- Clique Trees and VE
- BP In Practice
- Loopy BP and Message Decoding
Quiz
- Message Passing in Cluster Graphs
- Clique Tree Algorithm
Videos
- Max Sum Message Passing
- Finding a MAP Assignment
- Tractable MAP Problems
- Dual Decomposition - Intuition
- Dual Decomposition – Algorithm
Quiz
- MAP Message Passing
Videos
- Simple Sampling
- Markov Chain Monte Carlo
- Using a Markov Chain
- Gibbs Sampling
- Metropolis-Hastings Algorithm
Quiz
- Sampling Methods
- Sampling Methods PA Quiz
Video
- Inference in Temporal Models
Quiz
- Inference in Temporal Models
Video
- Inference Summary
Quiz
- Inference Final Exam
Instructors
Stanford Frequently Asked Questions (FAQ's)
The Probabilistic Graphical Models -2 programme will be completed in a time frame of 38 hours.
The candidates can access this programme in different languages namely, Spanish, Russian, English, Portuguese and French.
If you make the fee payment and complete the programme entirely then candidates will be awarded the certificate of completion.
The candidates get access to the 7-day free trial for this programme. Hence, they cannot apply for a refund in this.