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Slides for CMPS2200: Introduction to Algorithms

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All lecture slides are listed below. These are organized by module, each of which may contain one more more lectures.
Many are lectures are prepared using Jupyter, an interactive environment for coding and presenting. There are three ways to view these:

  1. live: runs a Jupyter notebook in the cloud so you can interact with the notes directly, using Binder
  2. static: view a static version of the notebook using nbviewer
  3. You can also clone this repo and launch the notebooks locally by running jupyter notebook (requires installing Jupyter and RISE).
topic
Module 01: Formalizing the cost of an algorithm
  Overview live/static
  Parallelism live/static
  Functional programming live/static
  SPARC live/static
  Cost models live/static
Module 02: Recurrences
  Recurrences live/static
Module 03: Sequences
  Sequences Overview live/static
  Iterate and Reduce live/static
  Scan live/static
  Problem solving with sequences live/static
Module 04: Divide and Conquer
  Reduction and Brute Force
  Divide & Conquer Scan
  MCSS + TSP Divide & Conquer
  Midterm Review
Module 05: Randomized Algorithms
  Probability Review
  Selection
  Quicksort
Module 06: Greedy Algorithms
  Task scheduling / Knapsack
  Heaps
  Huffman coding
Module 07: Dynamic Programming
  0-1 Knapsack
  Edit Distance, Longest Increasing Subsequence
  Huffman Coding
Module 08: Graphs
  Graph Overview
  BFS
  DFS
  Dijkstra
  Bellman-Ford
  Johnson
Module 09: Spanning trees
  MST Overview - Prim
  Kruskal+TSP
  Edge Contraction
  Star Contraction
  Boruvka
Module 10: Computability
  Computational Complexity

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