Bayesian Methods and Gaussian Processes
(DATASCI 226)
Fall 2024 (2-3 units)
This course provides an introduction to Bayesian statistics, Markov Chain Monte Carlo (MCMC) sampling, and Gaussian Processes. The first two units cover the fundamentals of Bayesian methods and MCMC, and the final optional unit explores Gaussian processes. Students will gain practical skills in applying these techniques to real-world problems using R, STAN, and JAGS.
Objectives
At the conclusion of this course, students will be able to:
- Identify the foundational principles of Bayesian statistics.
- Apply Bayesian methods to parameter estimation and hypothesis testing.
- Implement MCMC algorithms for complex Bayesian models using STAN and JAGS.
- Apply Gaussian processes for regression and classification problems using R.
Prerequisites
Basic knowledge of probability and statistics (BIOSTAT 200 and BIOSTAT 208 equivalent). Programming skills in R (BIOSTAT 213 and BIOSTAT 214 equivalent). Some familiarity with calculus and linear algebra (especially for the extra Gaussian processes unit).
Faculty
Course Director: | John Kornak, PhD Professor of Epidemiology & Biostatistics email: [email protected] |
Format
Weekly lectures with demonstration and hands-on exercises. Lectures will be held on Tuesday, 1:30 to 3:00 PM, September 10 through December 3. Labs will be held on Thursdays, 1:00 PM - 2:30 PM, September 12 through December 5.
All course materials and handouts will be posted on the course's online syllabus.
Materials
TBA
Grading
TBA
Only UCSF students (defined as individuals enrolled in UCSF degree or certificate programs) will receive academic credit for courses. Official transcripts are available to UCSF students only. A Certificate of Course Completion will be available upon request to individuals who are not UCSF students and satisfactorily pass all course requirements.
To Enroll
ATCR and MAS students use the Student Portal
Students taking individual courses:
Fall 2024 Course Fees
How to pay (please read before applying)
Fall 2024 Course Schedule
Apply by September 6, 2024.
Only one application needs to be completed for all courses desired during the quarter.