- Lecture Notes:
- Lecture 1 – introduction
- Lecture 2 – asymptotic notation
- Lecture 3 – graphs and graph algos
- Lecture 4 – DAGs and scheduling algos
- Lecture 5 – Single-source shortest path and MST
- Lecture 6 – More MST, Clustering & Divide-and-Conquer
- Lecture 7 – D&C multiplication and suffix array construction
- Lecture 8 – Introduction to DP & weighted interval scheduling
- MIDTERM 1
- Lecture 9 – Edit distance and sequence alignment
- Lecture 10 – Alignment with general gap penalties and in linear space
- Lecture 11 – General shortest paths and Bellman Ford
- Lecture 12 – Intro to Max Flow and FF algorithm
- Lecture 13 – EK and Maximum Bipartite Matching
- Lecture 14 – Disjoint Paths and Circulation with Demands
- Lecture 15 – Complexity and NP-completeness
- Lecture 16 – Complexity and NP-completeness 2
- Lecture 17 – Complexity and NP-completeness 3
- Lecture 18 – Approximation Algorithms 1
- Lecture 19 – Approximation Algorithms 2
- Lecture 20 – Other topics and wrap-up