BS in Applied and Computational Mathematics
Data Science Concentration Requirements
Lower Division Requirements
A. Complete the following Lower-Division Requirements:
Math 2A - Single-Variable Calculus I
Math 2B - Single-Variable Calculus II
Math 2D - Multivariable Calculus I
Math 2E - Multivariable Calculus II
Math 3A - Introduction to Linear Algebra
Math 3D - Elementary Differential Equations
Math 9 - Introduction to Programming for Numerical Analysis
Math 13 - Introduction to Abstract Mathematics
B. Complete the following lower-division courses:
Math 10 - Introduction to Programming in Data Science
Stats 7 - Basic Statistics
Physics 7C - Classical Mechanics
Upper Division Requirements
A. Complete the following Upper-Division Requirements:
Math 105A/105LA - Numerical Analysis I & Lab
Math 105B/105LB - Numerical Analysis II & Lab
Math 110A - Optimization I
Math 110B - Optimization II
Math 121A - Linear Algebra I
Math 121B - Linear Algebra II
Math 130A - Probability I
Math 130B - Probability II
Math 140A - Elementary Analysis I
Math 140B - Elementary Analysis II
B. Complete five electives from the below list. At least least one course must be outside of Mathematics; other options may be chosen in consultation with the Data Science concentration advisor:
Math 115 - Mathematical Modeling
Math 117 - Dynamical Systems
Math 118 - Theory of Differential Equations
Math 120B - Introduction to Abstract Algebra: Rings and Fields
Math 130C - Stochastic Processes
Math 134A - Fixed Income
Math 134B - Mathematics of Financial Derivatives
Math 140C - Analysis in Several Variables
Math 147 - Complex Analysis
Math 162A - Introduction to Differential Geometry I
Math 162B - Introduction to Differential Geometry II
Math 173A - Introduction to Cryptology I
Math 173B - Introduction to Cryptology II
Math 175 - Combinatorics
Math 176 - Mathematics of Finance
Math 178 - Mathematical Machine Learning
Stats 110 - Statistical Methods for Data Analysis I
Stats 111 - Statistical Methods for Data Analysis II
Compsci 171 - Introduction to Artificial Intelligence
Compsci 172B - Neural Networks and Deep Learning
Compsci 177 - Applications of Probability in Computer Science
Compsci 178 - Machine Learning and Data-Mining
Compsci 179 - Algorithms for Probabilistic and Deterministic Graphical Models
Compsci 183 - Introduction to Computational Biology
Compsci 184A - Artificial Intelligence in Biology and Medicine
Compsci 184C - Computational Systems Biology