Algorithms: Design and Analysis, Part 1

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What Will You Learn?

"Big-oh" notation
Sorting and searching
Divide and conquer (master method, integer and matrix multiplication, closest pair)
Randomized algorithms (QuickSort, contraction algorithm for min cuts)
Data structures (heaps, balanced search trees, hash tables, bloom filters)
Graph primitives (applications of BFS and DFS, connectivity, shortest paths)

About This Course

Provider: Edx
Format: Online
Duration: 24 hours to complete [Approx]
Target Audience: Intermediate
Learning Objectives: After completing this free course learners will be able to master the fundamentals of algorithms through several types of assessments.
Course Prerequisites: Basic programming skills in a language such as Python, Java, or C
Assessment and Certification: Earn a Certificate upon completion from the relevant Provider
Instructor: Standford Online
Key Topics: Algorithms, Matrix Multiplication, Master Theorem, Divide And Conquer, Data Structures, Bloom Filter, Computer Science
Topic Covered: 
  1. - Introduction
  2. - Asymptotic Analysis
  3. - Divide & Conquer Algorithms
  4. - The Master Method
  5. - Quicksort - Algorithm
  6. - Quicksort - Analysis
  7. - Probability Review
  8. - Linear-Time Selection
  9. - Graphs and the Contraction Algorithm
  10. - Graph Search and Connectivity
  11. - Dijkstra's Shortest-Path Algorithm
  12. - Heaps
  13. - Balanced Binary Search Trees
  14. - Hashing: The Basics
  15. - Universal Hashing
  16. - Bloom Filters
  17. - Final Exam

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