COGS 118ASupervised Machine Learning Algorithms
This course introduces the mathematical formulations and algorithmic implementations of the core supervised machine learning methods. Topics in 118A include regression, nearest neighborhood, decision tree, support vector machine, and ensemble classifiers. COGS 118A-B may be taken in either order.
Prerequisites
From the catalog: “COGS 18 or CSE 8B or CSE 11 and MATH 18 or MATH 31AH and MATH 20E and MATH 180A and COGS 108 or COGS 109 or COGS 118B or CSE 150 or CSE 151 or CSE 158 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 (3)
- Artificial Intelligence
- Cognitive Science (B.S.)
- Cognitive Science with Specialization in Clinical Aspects of Cognition (B.S.)
Courses that list COGS 118A as a prerequisite (8)
- COGS 118B Introduction to Machine Learning
- COGS 118D Computational Modeling and Analysis of Human Behavior
- COGS 181 Neural Networks and Deep Learning
- COGS 183 Generative AI
- COGS 185 Advanced Machine Learning Methods
- COGS 188 Artificial Intelligence Algorithms
- COGS 189 Brain Computer Interfaces
- CSE 151B Deep Learning