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Tentative Course Offerings

These are tentative schedules. Classes and/or instructors may change or be canceled. Please consult the official Schedule of Classes on TritonLink each quarter.

Featured Courses

Cogs 260: Seminar on Special Topics - Fall 2020

COGS 260 (C00): The 4E’s plus: Embodied, Enactive, Embedded and Extended... | Professor David Kirsh

This course is an exploration of recent rebellions against a classical view of mind that still, in many respects, dominates cognitive science.  The lectures start with a sympathetic statement of the classical view as advanced by Marr, Chomsky, Fodor and Newell and Simon plus a few more recent incarnations.  This is the non-strawman target position. It treats the human cognitive system to be functionally organized with major components solving core informational problems such as seeing or perceiving scenes, identifying what or who is where, understanding and generating language, social cognition, planning and reasoning, predicting future states of the environment, and legions of other functions like facial recognition that we regard as central to being human.  After reviewing this position subsequent lectures describe and evaluate the different E’s – Embodied, Enactive, Embedded, Extended mind and also the common inspiration derived from Situated Cognition and Distributed Cognition. Throughout, we necessarily lean on philosophy insofar as the proponents have usually been philosophers. But our goal is to evaluate the empirical contributions inspired by these metaphysical or methodological positions.  The professor will lecture for half the class, but student participation is central throughout.  

Class meets every Monday 11am-1:50pm online.


COGS 260 (A00): Cognitive Science Graduate Bootcamp | Professor Doug Nitz

For incoming doctoral students in cognitive science. During the first two weeks in September, students commit to ten to fifteen hours per day in lectures and workshops on the history of cognitive science, language and culture, machine learning and neural computation, neuroscience, design and human-computer interaction, programming and statistics, data science, ethnography, and clinical aspects of cognition. Students will attend weekly seminars during fall quarter. S/U grades and 2 units only.

Prerequisites: graduate (PhD) standing only; for students in the following major code CG75.

Cogs 260: Seminar on Special Topics - Winter 2021

COGS 260 (A00): Scientific Writing | Professor Anastasia Kiyonaga

This is a workshop and practical seminar for effective scientific writing. The course will address the fundamentals of getting words on the page, as well as techniques to make your writing stand out. The course is geared toward developing and revising a research writing project. Students should have a writing project in mind (e.g., journal article, thesis, or grant proposal in prep) and be willing to share drafts with classmates.

Class meets Mondays 11am-1:50pm online.


COGS 260 (D00):Probabilistic Machine Learning | Professor Marcelo G Mattar

This course is an introduction to Probabilistic Machine Learning. Topics include probability theory, regression and classification, graphical models, Expectation Maximization, appropriate inference, and sampling methods. The course will meet once a week and follow the textbook "Pattern Recognition and Machine Learning", by Christopher Bishop. Each week, 1-2 students will lead the discussion of one chapter of the book. Please contact Prof. Mattar at if you have questions.

Class meets every Thursday 2pm-4:50pm online.

Cogs 209: Scientific Data Analysis and Statistical Learning - Spring 2021

COGS 209 : Scientific Data Analysis and Statistical Learning | Professor Eran Mukamel

 Advanced statistical methods for learning from data. Model selection, evaluation, bias-variance tradeoff, multiple comparisons/false discovery rate, clustering, linear and non-linear multiple regression. 
This course will meet the Stats requirement for CogSci PhD students.
The course will include hands-on problem sets using Python to analyze cognitive science and neuroscience-related datasets.
Questions? Contact Prof. Mukamel at

Cogs 260: Seminar on Special Topics - Spring 2021

COGS 260 (A00): Collective Intelligence | Professor Steven Dow 

How can people and computers work together intelligently to solve complex problems? Collective intelligence is the study of how individuals coordinate, collaborate, and deliberate to produce outcomes greater than any single person do can alone. In this course, students will explore different platforms and mechanisms, discuss ethical and cultural issues, and conduct novel research that contributes to the literature on collective intelligence, crowdsourcing and human computation.  Students will complete homework assignments, discuss key research papers in the field, and create innovative research projects that could lead to publication.   Learn more:

Dsgn 274: Mobile Health Sensing - Spring 2021

DSGN 274: Mobile Health Sensing | Professor Edward Wang 

This class introduces students to the topic of mHeath Sensing. Topical readings curated by the instructor covers topics from machine learning techniques for understanding human emotions through mobile device usage to IoT sensors to monitor flu outbreaks. Lectures introduces methods of design and testing of mHealth sensing solutions, with assignments and final project providing hands-on practicum. To engage effectively, students will need prior familiarity with data processing with Python.

Course Pre-Authorizations

All COGS course pre-authorizations and prerequisite override requests must be made through the UC San Diego Enrollment Authorization System (EASy).