Intro to Algorithms (Udacity)

Intro to Algorithms (Udacity)
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Intro to Algorithms (Udacity)
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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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. By the end of this class, you will understand key concepts needed to devise new algorithms for graphs and other important data structures and to evaluate the efficiency of these algorithms.




Syllabus


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).



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MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Free Course

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.