Computational Cognitive Science Track
This is a specialized track within the PhD program in Cognitive Science.
Students entering this track should already have programming and math skills that would allow them to take the basic computation courses (e.g. experience with python or MATLAB, linear algebra, calculus, etc.). Visit the Cognitive Science PhD program admissions web page.
Students in this track will obtain a depth of focus in computational coursework, not achieved in the PhD in Cognitive Science general requirements. Accordingly, some of the breadth coursework with basic computational courses have been replaced, while aiming to retain the spirit of the breadth requirement.
- Breadth (3-4 courses): These courses should be offered by the Department of Cognitive Science and they must satisfy the following requirements:
- At least one course in each of language and vision areas
- Collectively develop sophistication in both:
- Theoretical approaches to cognitive science (e.g. theory in linguistics/psychology)
- (Human) experimental approaches to cognitive science
- Basic computation (3 courses): Machine learning, Foundations of Neural Network Theory, Bayesian Inference, Mathematical Models of Language, Data science
- Integration: Foundations of Cognitive Science
- Responsible Conduct in Research
- Depth: 6-8 courses that develop depth and expertise in specific areas of computational cognitive science. For example, Prof. Eisner’s Natural Language Processing course, Prof. Yuille’s Probabilistic Models of the Visual Cortex course, etc.
Coming Soon: Degree checklist for the Computational Cognitive Science Track within the PhD program in Cognitive Science.