Probabilistic Graphical Models: Principles and Techniques
Fee may apply
Learn important probabilistic modeling languages for representing complex domains and how the graphic models extend to decision making. Use ideas from discrete data structures in computer science to efficiently encode and manipulate probability distributions over high-dimensional spaces. Apply the basics of the Probabilistic Graphical Model representation and learn how to construct them, using both human knowledge and machine learning techniques to reach conclusions and make good decisions under uncertainty.
Basic probability theory and algorithm design and analysis.
- Bayesian and Markov networks
- Exact and approximate probabilistic inference algorithms
- Speech recognition
- Biological modeling and discovery
- Message encoding
- Medical diagnosis
- Robot motion planning
Note on Course Availability
This course is typically offered Winter quarter.
The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.
|Dates:||January 6 - March 13, 2020|
Provides Stanford University credit that may later be applied towards a graduate degree or certificate. Includes access to online course materials and videos for the duration of the academic quarter. Starting Autumn 2016 there is a $100 fee per course for courses dropped before the drop deadline. Click here for more information about our Registration Policies.
NotesEnrollment Dates: October 27 to December 9, 2019
Note: A wait list will open after this course reaches its capacity for enrollments. In the case that a spot becomes available, Student Services will contact you. Make sure you have submitted your NDO application and required documents to be considered.
Computer Science Department Requirement
Students taking graduate courses in Computer Science must enroll for the maximum number of units and maintain a B or better in each course in order to continue taking courses under the Non Degree Option.
This course may not currently be available to learners in some states and territories.