About this Course

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.

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Intro to Algorithms
Course Cost
Free
Timeline
Approx. 4 months
Skill Level
Intermediate
Included in Course
  • Icon course 01 3edf6b45629a2e8f1b490e1fb1516899e98b3b30db721466e83b1a1c16e237b1 Rich Learning Content

  • Icon course 04 2edd94a12ef9e5f0ebe04f6c9f6ae2c89e5efba5fd0b703c60f65837f8b54430 Interactive Quizzes

  • Icon course 02 2d90171a3a467a7d4613c7c615f15093d7402c66f2cf9a5ab4bcf11a4958aa33 Taught by Industry Pros

  • Icon course 05 237542f88ede3178ac4845d4bebf431ddd36d9c3c35aedfbd92e148c1c7361c6 Self-Paced Learning

  • Icon course 03 142f0532acf4fa030d680f5cb3babed8007e9ac853d0a3bf731fa30a7869db3a Student Support Community

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This free course is your first step towards a new career with the Machine Learning Engineer Nanodegree Program.

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Intro to Algorithms

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Course Leads

  • Michael Littman
    Michael Littman

    Instructor

What You Will Learn

Lesson 1

A Social Network Magic Trick

  • Become familiar with algorithm analysis.
  • Eulerian Path and Correctness of Na.
  • Russian peasants algorithm and more.
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 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 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 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 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 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).
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).

Prerequisites and Requirements

This class assumes an understanding of programming at the level of CS101, including the ability to read and write short programs in Python; it also assumes a comfort level with mathematical notation at the level of high school Algebra II or the SATs.

See the Technology Requirements for using Udacity.

Why Take This Course

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.

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals
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