Program DetailsPhD Programs
Location of Program
The curriculum for the Machine Learning Ph.D. is built on a foundation of five core courses and one elective (plus the Data Analysis Project requirement). These six courses also comprise the required courses for the MS degree. Together with the Data Analysis Project requirement, these should be completed during the first three years of study.
A typical full-time, graduate course load during the first two years consists each term of two classes (at 12 graduate units per class) plus 24 units of advanced research. Thus, during the first two years, a student has the opportunity to take several elective classes in addition to the six required courses.
The ML curriculum joins courses with a Computer Science main theme and those with a Probability and Statistics main theme. These may be grouped, as follows:
In CS, relevant sub-fields include: Databases, Machine Learning, Data Mining, and Algorithms applications in areas such as Robotics, Informa