CS-101: Advanced information, computation, communication I

Lectures in this course (309)

Introduces sets and functions, covering union, intersection, complement, functions terminology, and set operations analogies.

Covers the basics of propositional logic, its history, language, and computing applications.

Introduces sets, functions, and their properties, including injective and surjective functions, composition, and inverse functions.

Introduces binary relations, functions, and various types of relations in sets.

Explores translating natural language to propositional logic, Boolean search, logic puzzles, circuits, and Sudoku.

Explores equivalence relations, functions, subsets, and De Morgan's laws.

Introduces equivalence relations, partitions, partial orderings, and total ordering concepts with examples and definitions.

Covers topics on relations, sequences, and summations, including lattices, recurrence relations, and sigma notation.

Covers strings, countable sets, cardinality, and the concept of countability, exploring the countability of various sets and Cantor diagonalization.

Explains variables, predicates, propositional functions, and quantifiers in predicate logic.

Introduces posets, Hasse diagrams, and equivalence relations on sets.

Explores optimization problems and greedy algorithms to find the best solutions efficiently.

Covers the basics of propositional logic and explores logical equivalences and proof techniques.

Explores the optimality of the greedy change-making algorithm and the stability of maximum matching.

Explores quantifiers with finite domains, uniqueness quantifier, composite statements, variable binding, and validity in logic.

Explores linear search, insertion sort, coin change, maximum matching, and the halting problem in algorithms.

Covers the Big-O notation to analyze algorithm efficiency and provides examples of polynomial and factorial function estimates.

Explores the complexity of algorithms, including big-O notation and efficiency analysis.

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Covers logical equivalences, quantifiers, and De Morgan's Laws in predicate logic.

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