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Your search for courses for 19/WI and in CMC 301 found 4 courses.
CS 111.02 Introduction to Computer Science 6 credits
Closed: Size: 34, Registered: 34, Waitlist: 0
| M | T | W | TH | F |
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| 11:10am12:20pm | 11:10am12:20pm | 12:00pm1:00pm |
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Sophomore Priority
Waitlist for Juniors and Seniors: CS 111.WL2 (Synonym 51313)
CS 252.00 Algorithms 6 credits
Closed: Size: 34, Registered: 34, Waitlist: 0
| M | T | W | TH | F |
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| 8:30am9:40am | 8:30am9:40am | 8:30am9:30am |
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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: 33, Waitlist: 0
| M | T | W | TH | F |
|---|---|---|---|---|
| 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 111 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202)
CS 364.00 Molecular Programming and Nanoscale Self-Assembly 6 credits
Open: Size: 34, Registered: 12, Waitlist: 0
| M | T | W | TH | F |
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| 12:30pm1:40pm | 12:30pm1:40pm | 1:10pm2:10pm |
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Algorithms are ubiquitous in nature and are even present in biological and chemical processes. For example, cells receive molecular signals, execute procedures, and send signals of their own, and chemical reactions compute functions by transforming reactants into products according to molecular rules. In this course, we will investigate various mathematical models of chemistry, biology, and nanoscale self-assembly. We will use each model as a programming language to compute molecular algorithms, verify their correctness, and analyze their complexity and robustness. We will also discover that many of these models are algorithmically universal and are equivalent in power to modern programming languages.
Prerequisite: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202). No background in biology or chemistry is required, but it may be helpful
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