Free Course
Intro to Algorithms
School Of Programming and Development
This class will give you an introduction to the design and analysis of algorithms, enabling you to analyze networks and discover how individuals are connected.
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Intro to Algorithms
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Certification
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Course Details
Course Details Free
Timeline Approx. 4 Months
Skill Level Intermediate
Included in Product
Rich Learning Content
Taught by Industry Professionals
Student Support Community
Interactive Quizzes
Self-Paced Learning
Intro to Algorithms
Ever played the Kevin Bacon game? This class will show you how it works by giving you an introduction to the design and analysis of algorithms, enabling you to discover how individuals are connected.
Course Leads
Michael Littman
InstructorSyllabus
lesson 1
A Social Network Magic Trick
- Become familiar with algorithm analysis.
- Eulerian Path and Correctness of Na.
- Russian peasants algorithm and more.
lesson 2
Growth Rates in Social Networks
- Use mathematical tools to analyze how things are connected.
- Chain, ring and grid networks.
- Big Theta and more.
lesson 3
Basic Graph Algorithms
- Find the quickest route to Kevin Bacon.
- Properties of social networks.
- Clustering coefficient and more.
lesson 4
It's Who You Know
- Learn to keep track of your best friends using heaps.
- Degree centrality.
- Top K Via Partitioning and more.
lesson 5
Strong and Weak Bonds
- Work with social networks that have edge weights.
- Make a tree and strength of connections.
- Weighted social networks and more.
lesson 6
Hardness of Network Problems
- Explore what it means for a social network problem to be "harder" than other.
- Tetristan and Exponential Running Time
- Degrees of hardness and more.
lesson 7
Review and Application
- Interview with Peter Winker (Professor, Dartmouth College) on names and boxes problem and puzzles and algorithms.
- Interview with Tina Eliassi-Rad (Professor, Rutgers University) on statistical measures in network and social networks in security and protests.
- Additional interviews with Andrew Goldberg (Microsoft Research), Vukosi Marivate (Rutgers University) and Duncan Watts (Microsoft).