MATH 213-A1 - Introduction to Discrete Mathematics (Spring 2026)
| General Information |
Homework |
Lecture Notes |
Other Resources |
This course provides an introduction to basic discrete mathematics with an emphasis on algorithms. Topics include sets and functions, algorithms, induction, enumeration, probability, relations, graphs, and trees.
| Lecture | MWF 1:00pm-1:50pm
Everitt Lab 3117 |
| Textbook | Kenneth H. Rosen.
Discrete Mathematics and Its Applications, 7th edition |
| Instructor | Andrew Hardt
Email: ahardt@illinois.edu
Office Hours: W 2:00pm-2:50pm, F 11:00am-11:50am, Harker Hall 204C
Problem Sessions: M 2:00pm-3:20pm, Everitt 2101 |
| More Details | Syllabus | Gradescope | If you can't access the Gradescope course, email me |
Homework assignments are weekly, due at 9:00am on Wednesdays via Gradescope. Using LaTeX for your homework is encouraged, and you will receive 1 bonus point for each homework you typeset using LaTeX.
Here is a short LaTeX tutorial video (from Fall 2024).
- Lectures 1 and 2 (1/21, 1/23): Propositional logic (and, or, not, implies), conjunctions/disjunctions, truth tables, sets, set operations, Venn diagrams
- Lecture 3 (1/26): Complement, cardinality, membership tables, proof techniques
- Lecture 4 (1/28): Venn diagrams and set identities, functions
- Lecture 5 (1/30): Functions: domain/codomain/image/inverse image, injectivity, surjectivity, inverse functions
- Lecture 6 (2/2): Introduction to Algorithms
- Lecture 7 (2/4): Sorting algorithms, Big-O Notation
- Lecture 8 (2/6): Proofs for Big-O Notation, Mathematical Induction
- Lecture 9 (2/9): Mathematical Induction and Strong Induction
- Lecture 10 (2/11): Strong Induction (cont.), Counting Basics
- Lecture 11 (2/13): More Counting, and the Pigeonhole Principle
- Lecture 12 (2/15): Midterm 1 Review
- Lecture 13 (2/20): Pigeonhole Principle (cont.), Permutations and Combinations
- Lecture 14 (2/23): Binomial coefficients and identities
- Lecture 15 (2/25): Generalized permutations and combinations
- Lecture 16 (2/27): Introduction to probability
- Lecture 17 (3/2): Conditional probability, independence, Bernoulli trials, Bayes' Theorem
- Lecture 18 (3/4): Bayes' Theorem (cont.)
- Lecture 19 (3/6): Recurrence relations
- Lecture 20 (3/9): Solving linear recurrence relations
- Lecture 21 (3/11): Inclusion-exclusion
Important Course Events
Midterm Exam 1: Wednesday, 2/18, in class (Solutions)
Midterm Exam 2: Wednesday, 4/1, in class
Midterm Exam 3: Wednesday, 4/29, in class
Final Exam: Tuesday, 5/12 -- 8:00am-11:00am, location TBD
Problem Sessions: Mondays, 2:00pm-3:20pm, Everitt 2101
Links