- To prepare students for studying the subsequent courses which use the set-theoretic, combinatorial, graph or probability formalism.
- To teach students how to identify a typical problem of Discrete Mathematics in a problem given, either applied or theoretical.
- Students will master basic concepts and methods of Discrete Mathematics as far as these are necessary for studying more advanced courses and for the future professional life.
- Students will develop skills in formalizing and solving applied problems using the methods of Discrete Mathematics.
- Propositional and predicate logic (an informal treatment). Main set-theoretic constructions. Algebra of sets. Cartesian product.
- Induction principle. Fundamental theorem of arithmetic. Euclidean algorithm. Continued fractions. Modular arithmetic. Linear congruences and Diophantine equations. Chinese remainder theorem. Fermat's little theorem, Euler’s theorem.
- Algebra of binary relations. Image of set. Special binary relations. Functions, bijections. Set equivalence. Indicator functions. Cantor’s theorem. Cantor–Schröder–Bernstein theorem. Cardinalities of sets \N^2, \Z, \Q, \R^2, \N^\N, \R^\N.
- Pigeonhole principle. Finite and countable sets. Countable union of countable sets. Rules of sum and product. Number of functions, injections, bijections. Number of subsets, binomial coefficients and their properties. Binomial and multinomial theorems. Multisets. Inclusion–exclusion principle with applications (surjections, derangements, Euler’s totient function).
- Special binary relations. Orderings. Order isomorphism. Lattices; chains and antichains. Equivalences and partitions. Counting chains and partitions for finite sets (Dilworth's theorem etc.).
- Graphs. Vertex degree. Isomorphism. Bipartite graphs. Matchings. Connected components. Trees. Spanning tree. Eulerian and Hamiltonian paths. Directed graphs. De Bruijn graphs.
- Formal languages. Monoid of words. Prefixes and suffixes. Semiring of languages. Inductive definitions. Regular bracket sequences and Catalan numbers.
- Classical probability model. Conditional probability, Bayes’ theorem. Random variable. Expectation and variance. Some inequalities. Combinatorial applications.
- Boolean functions and circuits. Clones. Functional completeness. Counting functions of various classes.
- Final examA final written exam with open questions.
- HomeworkAverage grade for the homework will be included into the cumulative grade.
- ColloquiumsThe grade for the colloquium will be included into the cumulative grade.
- Cumulative Grade
- Discrete mathematics, Biggs N. L., 2004
- Lovász, L., Pelikán, J., & Vsztergombi, K. (2003). Discrete Mathematics : Elementary and Beyond. New York: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=108108