COGS 118DComputational Modeling and Analysis of Human Behavior
Behavioral data is everywhere and reveals how we think, learn, and act. This course equips you to analyze, model, and predict behavior using tools from machine learning. We will explore a variety of computational models, including Bayesian models, latent variable models, and time series analysis, and apply them to real-world datasets. A practical course for students interested in behavioral data science or computational research in human behavior.
Prerequisites
From the catalog: “MATH 18 or MATH 31AH and MATH 180A or MATH 183 or MATH 186 or ECE 109 or ECON 120A or MAE 108 and COGS 108 or COGS 109 or COGS 118A or COGS 118B or COGS 188 or CSE 150A or CSE 151A or CSE 158 or CSE 158R or DSC 148 or ECE 174 or ECE 175A.”
Where it sits in degree plans
Required in (3)
- Cognitive Science with Specialization in Design and Interaction (B.S.)
- Cognitive Science with Specialization in Language and Culture (B.S.)
- Cognitive Science with Specialization in Machine Learning and Neural Computation (B.S.)
One of the options in (2)
- Cognitive Science (B.S.)
- Cognitive Science with Specialization in Clinical Aspects of Cognition (B.S.)
Courses that list COGS 118D as a prerequisite (9)
- CSE 150A Introduction to Artificial Intelligence: Probabilistic Reasoning and Decision-Making
- CSE 150B Introduction to Artificial Intelligence: Search and Reasoning
- CSE 151A Machine Learning: Learning Algorithms
- CSE 151B Deep Learning
- CSE 153 Machine Learning for Music
- CSE 153R Machine Learning for Music
- CSE 156 Statistical Natural Language Processing
- CSE 158 Recommender Systems and Web Mining
- CSE 158R Recommender Systems and Web Mining