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Mathematical and Computational Science Electives (9 Units)

Three courses in mathematical and computational science, 100-level or above, at least 3 units each. At least one must be chosen from the following:

 

Qtr. and Units

ECON 102C. Advanced Topics in Econometrics

S

5

ECON 140. Introduction to Financial Economics

W,S

5

ECON 160. Game Theory and Economic Applications (not given 2009-10)

 

5

(prerequisite ECON 51)

 

 

ECON 179. Experimental Economics

W

5

EE 261. The Fourier Transform and its Applications

A,W

3

EE 263. Introduction to Linear Dynamical Systems

W

3

EE 278. An Introduction to Statistical and Signal Processing

 

3

MS&E 211. Linear and Nonlinear Optimization

A

3-4

MS&E 212. Mathematical Programming
and Combinatorial Optimization

W

3

MS&E 221. Stochastic Modeling

W

3

MS&E 251. Stochastic Decision Models (not given 2009-10)

 

3

MCS 100. Mathematics of Sports (same as STATS 50)

A

3

MATH 104. Applied Matrix Theory

A, W

3

MATH 106. Functions of a Complex Variable

A

3

MATH 108. Introduction to Combinatorics
and its Applications

A

3

MATH 113. Linear Algebra & Matrix Theory

W,S

3

MATH 115. Functions of a Real Variable

A,W

3

MATH 116. Complex Analysis

W

3

MATH 131. Partial Differential Equations I

A,W

3

MATH 132. Partial Differential Equations II

S

3

MATH 136. Stochastic Processes

 

3

MATH 171. Fundamental Concepts of Analysis

A,S

3

MATH 172. Lebesgue Integration and Fourier Analysis

S

3

PHIL 151. First-Order Logic

W

4

STATS 202. Data Analysis

A

3

STATS 208. Introduction to the Bootstrap (not given 2009-10)

 

 

STATS 215. Statistical Models in Biology

W

3

STATS 217. Introduction to Stochastic Processes

W

3

For Computer Science (CS), electives can include courses not taken as units under the CS list above and the following:

CME 302. Numerical Linear Algebra

A

3

CS 108. Object-Oriented Systems Design

A,W

3-4

CS 110. Principles of Computer Systems

W,S

5

CS 140. Operating Systems and Systems Programming

W,S

3-4

CS 143. Compilers

A

3-4

CS 157. Logic and Automated Reasoning

A

3-4

CS 161. Design and Analysis of Algorithms

A,W

3-4

CS 164. Computing with Physical Objects

 

3

CS 194. Software Project (prerequisite CS 108)

S

3

CS 221. Artificial Intelligence: Principles and Techniques

A

3-4

CS 223A. Introduction to Robotics

W

3

CS 223B. Introduction to Computer Vision

W

3

CS 225A. Experimental Robotics

S

3

CS 228. Probabilistic Models in Artificial Intelligence

W

3

CS 229. Machine Learning

A

3

CS 243. Advanced Compiling Techniques

W

3-4

EE 282. Computer Systems Architecture

S

3

With the adviser's approval, courses other than those offered by the sponsoring departments may be used to fulfill part of the elective requirement. These may be in fields such as biology, economics, electrical engineering, industrial engineering, and medicine, that might be relevant to a mathematical sciences major, depending on a student's interests.

  1. At least three quarters before graduation, majors must file with their advisers a plan for completing degree requirements.
  2. All courses used to fulfill major requirements must be taken for a letter grade with the exception of courses offered satisfactory/no credit only.
  3. A course used to fulfill the requirements of one section of the program may not be applied toward the fulfillment of the requirements of another section.
  4. The student must have a grade point average (GPA) of 2.0 or better in all course work used to fulfill the major requirement.

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