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IS 597 DSO - Adv Topics Data An & Data Sci - Data Structures & Algorithms

Campus: Urbana-Champaign


Variety of newly developed and advanced topics courses within the fields of Data Analytics & Data Science, intended to augment the existing Information Sciences curricula. Course Information: 2 to 4 graduate hours. No professional credit. Approved for Letter and S/U grading. May be repeated in the same or separate semesters to a maximum of 16 hours, if topics vary.

Special Instructions:

Prerequisite: -At least three previous programming courses including 590PR/597PR, or instructor approval, email your request to jweible@illinois.edu. - Learn, experiment, code with, and compare performance of common data structures and algorithms in a fun, collaborative, and challenging context. In class, students will solve or play and discuss several types of logic puzzles and strategy games. In small teams they will explore the deductive, strategic, and tactical decisions involved, select appropriate data structures & algorithms to develop efficient program solutions to automate playing, solving, generating, or analyzing puzzles & games. Techniques used include analysis of efficiency (Big-O, Big-theta), recursion, minimax, Monte Carlo Tree Search, client/server network communications, deterministic vs non-deterministic algorithms. Structures used include arrays, matrices, hash tables, stacks, various trees, network graphs, and custom structures. For some projects, students will

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 4

Term(s): Fall , Spring


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