README.md

Coursera-Stanford-Divide-and-Conquer-Sorting-and-Searching-and-Randomized-Algorithms

Course can be found in Coursera

Quiz answers and notebook for quick search can be found in my blog SSQ

• Week 1 Lecture slides:

  • 1: Divide and Conquer:
    • Integer Multiplication;
    • Karatsuba Multiplication;
    • Implementation by Python;
    • Merge Sort.
  • 2: Asymptotic Analysis:
    • Big-oh notation; Omega and Theta notation;

• Week 2 Lecture slides:

  • 3: Divide and Conquer:
    • Counting Inversions
    • Implementation by python;
    • Matrix Multiplication Strassen’s Algorithm
    • Closest Pair Optional
  • 4: The Master Method:
    • Motivation; Example; Proof I, Proof II

• Week 3 Lecture slides:

  • 5: Randomized Algorithm - QuickSort:
    • Overview; The Partition Subroutine; Proof; Choosing a Good Pivot
    • Implementation of QuickSort with 3 pivots by python
  • 6: QuickSort Analysis:
    • the average running time of QuickSort (with random pivots)
  • 7: Probability Review:

• Week 4 Lecture slides:

  • 8: Linear-time Selection
    • Randomized Selection
    • Deterministic Selection
  • 9: Graphs and The Minimum Cut
    • Random Contraction Algorithm
    • Implementation by Python