CS-101 / coefficient 7

Teacher(s): Bourgeat Thomas Emile, Käser Jacober Tanja Christina

Language: English

Remark: This course focuses on the foundational, discrete mathematics core of advanced computation.


Summary

Discrete mathematics is a discipline with applications to almost all areas of study. It provides a set of indispensable tools to computer science in particular. This course reviews (familiar) topics as diverse as mathematical reasoning, combinatorics, discrete structures & algorithmic thinking.

Content

I. Mathematical reasoning: propositional logic, propositional functions, quantifiers, rules of inference; this includes very basic logic circuits.
II. Sets and counting: cardinalities, inclusion/exclusion principle, sequences and summations.
III. Algorithms and complexity: basic algorithms, computational complexity, big-O notation and variants, countability.
IV. Number representations such as binary and hexadecimal and (postponed to 2nd semester) basic number theory: modular arithmetic, integer division, prime numbers, hash functions, pseudorandom number generation; applications.
V. Induction and recursion: mathematical induction, recursive definitions and algorithms.
VI. Basic combinatorial analysis: permutations, binomial theorem, counting using recursions.
VII. Basic probability: events, independence, random variables, Bayes' theorem.
VIII. Structure of sets: relations, equivalence relations, power set.

Keywords

Propositional logic, counting, complexity, big-O, number representations, sets, functions, relations, induction, basic probabilities, Bayes theorem, combinatorial analysis, recurrences, countability.

Learning Outcomes

By the end of the course, the student must be able to:

  • Recognize if there is a mistake in a (simple) proof
  • Apply general problem-solving techniques
  • Recognize the mathematical structures present in applications
  • Apply simple recursion and use it to design recursive algorithms
  • Apply the tools studied in class to solve problems
  • Demonstrate familiarity with mathematical reasoning
  • Solve linear recurrences and use generating functions
  • Argue about (un)countability
  • Formulate complete, clear mathematical proofs

Transversal skills

  • Assess one's own level of skill acquisition, and plan their on-going learning goals.
  • Continue to work through difficulties or initial failure to find optimal solutions.
  • Demonstrate the capacity for critical thinking

Teaching methods

Ex cathedra lectures

Expected student activities

Studying the book, test your understanding by making the exercises, ask questions

Assessment methods

Continuous evaluations 10% and final exam 90%

Supervision

Office hours No
Assistants Yes
Forum No
Others Additional Q&A sessions will take place on Tuesdays from 17:15-18:30 in INM 200 (starting in the second week of the semester)

Resources

Bibliography

"Discrete Mathematics and Its Applications", Kenneth H. Rosen, 8th ed, McGraw-Hill 2019. (You should be able to find the pdf on the web.)

Ressources en bibliothèque

Websites

Moodle Link

In the programs

  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Advanced information, computation, communication I
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: mandatory
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Advanced information, computation, communication I
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: mandatory

Reference week

Tuesday, 8h - 10h: Lecture RLC E1 240

Wednesday, 15h - 17h: Lecture RLC E1 240

Friday, 10h - 12h: Exercise, TP INF119
INM201
INM202
INM203
INM10
INM11
CM011
CM1100
INJ218
INR219

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