Algorithmic Thinking

Rice University (Coursera)

Details

4 modules used in the course including Project files, Application files and any additional test files and support files for completing each module.

Includes

• Module 1 - Graphs Basics and Random Digraphs

  • Project -> Degree distributions for graphs
  • Application -> Analysis of citation graphs
  • Support: Images, DPA algorithms for creating DPA graph

• Module 2 - Breadth-First Search and Connected Components

  • Project -> Connected Components and Graph Resilience
  • Application -> Analysis of a Computer Network (incomplete)

• Module 3 - Divide and Conquer Method and Clustering

  • Project -> Closest Pairs and Clustering Algorithms
  • Application -> Comparison of Clustering Algorithms
  • Support: Images, Cluster Algorithm, Matplotlib Cluster Functions, Test File

• Module 4 - Dynamic Programming and Sequence Alignment

  • Project -> Computing Alignments of Sequences
  • Application -> Applications to Genomics and Beyond

Contributors

• Mark Hess
• Rice University
• Coursera