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Your search for courses for 23/WI and with code: MATHELEC found 9 courses.
CS 252.00 Algorithms 6 credits
Open: Size: 34, Registered: 27, Waitlist: 0
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| 1:50pm3:00pm | 1:50pm3:00pm | 2:20pm3:20pm |
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A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis.
Prerequisite: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202)
CS 254.00 Computability and Complexity 6 credits
Closed: Size: 34, Registered: 31, Waitlist: 0
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| 9:50am11:00am | 9:50am11:00am | 9:40am10:40am |
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An introduction to the theory of computation. What problems can and cannot be solved efficiently by computers? What problems cannot be solved by computers, period? Topics include formal models of computation, including finite-state automata, pushdown automata, and Turing machines; formal languages, including regular expressions and context-free grammars; computability and uncomputability; and computational complexity, particularly NP-completeness.
Prerequisite: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202)
MATH 240.00 Probability 6 credits
Closed: Size: 30, Registered: 31, Waitlist: 1
| M | T | W | TH | F |
|---|---|---|---|---|
| 11:10am12:20pm | 11:10am12:20pm | 12:00pm1:00pm |
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(Formerly Mathematics 265) Introduction to probability and its applications. Topics include discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions.
Prerequisite: Mathematics 120 or Mathematics 211
Formerly Mathematics 265
MATH 241.01 Ordinary Differential Equations 6 credits
Closed: Size: 25, Registered: 22, Waitlist: 1
| M | T | W | TH | F |
|---|---|---|---|---|
| 9:50am11:00am | 9:50am11:00am | 9:40am10:40am |
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Prerequisite: Mathematics 232 or instructor permission
MATH 251.00 Chaotic Dynamics 6 credits
Open: Size: 25, Registered: 19, Waitlist: 0
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|---|---|---|---|---|
| 11:10am12:20pm | 11:10am12:20pm | 12:00pm1:00pm |
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An exploration of the behavior of non-linear dynamical systems. Topics include one and two-dimensional dynamics, Sarkovskii's Theorem, chaos, symbolic dynamics,and the Hénon Map.
Prerequisite: Mathematics 232 or instructor permission
MATH 271.00 Computational Mathematics 6 credits
Closed: Size: 25, Registered: 28, Waitlist: 3
| M | T | W | TH | F |
|---|---|---|---|---|
| 1:50pm3:00pm | 1:50pm3:00pm | 2:20pm3:20pm |
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An introduction to mathematical ideas from numerical approximation, scientific computing, and/or data analysis. Topics will be selected from numerical linear algebra, numerical analysis, and optimization. Theory, implementation, and application of computational methods will be emphasized.
Prerequisite: Mathematics 232
Not open to students who have already received credit for Mathematics 295 Numerical Analysis
MATH 321.00 Real Analysis I 6 credits
Closed: Size: 23, Registered: 24, Waitlist: 10
| M | T | W | TH | F |
|---|---|---|---|---|
| 12:30pm1:40pm | 12:30pm1:40pm | 1:10pm2:10pm |
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Prerequisite: Mathematics 236 or instructor permission
MATH 352.00 Topics in Abstract Algebra 6 credits
Open: Size: 20, Registered: 17, Waitlist: 0
| M | T | W | TH | F |
|---|---|---|---|---|
| 11:10am12:20pm | 11:10am12:20pm | 12:00pm1:00pm |
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Prerequisite: Mathematics 342
This course can be repeated
STAT 250.00 Introduction to Statistical Inference 6 credits
Open: Size: 30, Registered: 27, Waitlist: 0
| M | T | W | TH | F |
|---|---|---|---|---|
| 9:50am11:00am | 9:50am11:00am | 9:40am10:40am |
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(Formerly Mathematics 275) Introduction to modern mathematical statistics. The mathematics underlying fundamental statistical concepts will be covered as well as applications of these ideas to real-life data. Topics include: resampling methods (permutation tests, bootstrap intervals), classical methods (parametric hypothesis tests and confidence intervals), parameter estimation, goodness-of-fit tests, regression, and Bayesian methods. The statistical package R will be used to analyze data sets.
Prerequisite: Mathematics 240 Probability (formerly Mathematics 265)
Formerly Mathematics 275
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