Section | 1 |
---|---|
Instructor(s) | Siegel, Andrew (siegela) |
Location | JCL 011 (In-Person or Online) |
Meeting Times | Monday 6pm - 8pm |
Fulfills | Elective Specialization - Data Analytics (DA-2) Specialization - High Performance Computing (HPC-2) |
In this class we focus on the rudimentary ideas and techniques that underlie stochastic time series analysis, discrete events modeling, and Monte Carlo simulations. Course lectures will focus on the basic principles of probability theory, their efficient implementation on modern computers, and examples of their application to real world problems. Upon completion of the course, students should have an adequate background to quickly learn in depth specific Monte Carlo approaches in their chosen field of interest.
Recommended Textbooks
Coursework
4 homework assignments (50%), 6 short quizzes (20%), two exams (30%).Core Programming, Recommended: Immersion Math or passing score on math placement exam.
Non-MPCS students need to complete a course request form. This course requires competency in Unix and Linux. Please plan to attend the MPCS Unix Bootcamp (https://masters.cs.uchicago.edu/page/mpcs-unix-bootcamp) or take the online MPCS Unix Bootcamp Course on Canvas.
For MPCS students, this is an elective/specialization course and can only be taken after completion of three core classes or concurrent with third core class.
This class is scheduled at a time that conflicts with these other classes: