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CSCI-C 241 Discrete Structures for Computer Science

3 credits

  • Prerequisites: None
  • Delivery: On-Campus
  • Induction and recursive programs, running time, asymptotic notations, combinatorics and discrete probability, trees and lists, the relational data model, graph algorithms, and propositional and predicate logic.

    Learning Outcomes

    1. Use logical notation to define and reason about fundamental mathematical concepts such as sets, relations, functions, and integers.
    2. Evaluate elementary mathematical arguments.
    3. Synthesize induction hypotheses and simple induction proofs.
    4. Prove elementary properties of modular arithmetic and explain their computer science applications.
    5. Apply graph theory models of data structures and state machines to solve problems of connectivity and constraint satisfaction.
    6. Apply invariants and well-founded ordering to prove the correctness and termination of processes and state machines.
    7. Derive closed-form and asymptotic expressions from series and recurrences for growth rates of processes.
    8. Calculate the number of possible outcomes of elementary combinatorial processes.
    9. Calculate probabilities and discrete distributions for simple combinatorial processes.
    10. Problem-solve in small teams.


    There is not a syllabus available for this course.