| Announcements | | Course information | | Labs | | Slides |
Instructor:
Antonina
Kolokolova
Textbook: (not required) Discrete Mathematics and Its Applications: Kenneth H. Rosen.
Reference books:
All course materials will be posted on Brightspace . You should be automatically enrolled when you register for the course; click Brightspace link to login (with your MUN id and password) to access the course shell. Quizzes, tests, etc will take place in Brightspace as well, and links for labs and tutorials, as well as lecture recordings and slides will be posted there. I will be using Brightspace for announcements, and Brightspace’s discussion board will be our main place to ask questions and get answers.
Marking scheme: TBA
Course description
Logic has been called the "calculus of computer science": just as sciences
such as physics that deal with continuous realm rely on calculus techniques,
we rely on logic. Indeed, so many areas of our field are based on logic: from
designing circuits to determining complexity of problems; from verifying
correctness of algorithms and devising database queries to automated
reasoning in artificial intelligence.
This course is intended to be an introduction to mathematical logic with emphasis on Computer Science applications and methodologies. We will cover propositional and predicate logic with applications, including the Resolution proof technique, which is the basis of most modern-day automated problem solvers. Then we will discuss basic proof techniques such as mathematical induction, again with computer science applications. We will also touch upon basic combinatorics, counting methods and probability, and theory of computation.
You are welcome to check the slides and other materials from one of the previous semesters.
Here is a guide from a famous mathematician Polya on how to approach solving problems.