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6.1200J | Spring 2024 | Undergraduate

# Mathematics for Computer Science

##### Lecture 1: Predicates, Sets, and Proofs

##### Lecture 2: Contradiction and Induction

##### Lecture 3: Casework and Strong Induction

##### Lecture 4: State Machines

##### Lecture 5: Sums

##### Lecture 6: Asymptotics

##### Lecture 7: Recurrences

##### Lecture 8: Divisibility

##### Lecture 9: Modular Arithmetic

##### Lecture 10: Cryptography

##### Lecture 11: Graphs and Coloring

##### Lecture 12: Matching

##### Lecture 13: Connectivity and Trees

##### Lecture 14: Digraphs and DAGs

##### Lecture 15: Relations and Counting

##### Lecture 16: Counting Techniques

##### Lecture 17: More Counting Techniques

##### Lecture 18: Probability

##### Lecture 19: Conditional Probability

##### Lecture 20: Independence

##### Lecture 21: Random Variables

##### Lecture 22: Expectation

##### Lecture 23: Expectation and Variance

##### Lecture 24: Large Deviations: Chebyshev and Chernov Bound, Wrap Up

## Course Info

##### Instructors

- Prof. Erik Demaine
- Dr. Zachary Abel
- Dr. Brynmor Chapman

##### Departments

- Electrical Engineering and Computer Science
- Mathematics

##### As Taught In

Spring 2024

##### Level

Undergraduate

##### Topics

- Engineering
  - Computer Science
    - Algorithms and Data Structures
- Mathematics
  - Computation

##### Learning Resource Types

theaters Lecture Videos
notes Lecture Notes
Readings
assignment Problem Sets
menu_book Open Textbooks

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