Intro to Algorithms (Udacity)

Offered by Udacity,
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.

Class Deals by MOOC List - Click here and see Udacity's Active Discounts, Deals, and Promo Codes.

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

Related Courses

Algorithms, Part I (Coursera) Coursera
Princeton University

Algorithms, Part I (Coursera)

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.

Sep 21st 2026
5-12 Weeks
Data Structures & Algorithms in Swift (Udacity) Udacity
Udacity

Data Structures & Algorithms in Swift (Udacity)

Confidently take on the tech interview. Technical interviews follow a pattern. If you know the pattern, you’ll be a step ahead of the competition. This course will introduce you to common data structures and algorithms in Swift. You'll review frequently-asked technical interview questions and learn how to structure your responses. You will answer practice problems and quizzes to test your abilities. Then you'll practice mock interviews to get specific recommendations for improvement. Be ready for anything the technical interviewer throws at you.

Self Paced
Self-Paced
HTTP & Web Servers (Udacity) Udacity
Udacity

HTTP & Web Servers (Udacity)

How does HTTP work? This course is intended for budding full-stack web developers to master the basics of HTTP, the protocol that underlies all web technology. In this course, you'll explore HTTP directly, talking with web servers and browsers by hand. You'll write and deploy low-level web applications in Python. And you'll learn more about how HTTP connects with other web technologies.

Self Paced
Self-Paced
Data Wrangling with MongoDB (Udacity) Udacity
Udacity,MongoDB University

Data Wrangling with MongoDB (Udacity)

In this course, we will explore how to wrangle data from diverse sources and shape it to enable data-driven applications. Some data scientists spend the bulk of their time doing this! Students will learn how to gather and extract data from widely used data formats. They will learn how to assess the quality of data and explore best practices for data cleaning. We will also introduce students to MongoDB, covering the essentials of storing data and the MongoDB query language together with exploratory analysis using the MongoDB aggregation framework.

Self Paced
Self-Paced
Intro to AJAX (Udacity) Udacity
Udacity

Intro to AJAX (Udacity)

Making Asynchronous Requests with jQuery. In this course you will learn how to make asynchronous requests with JavaScript (using jQuery’s AJAX functionality), and gain a better understanding of what’s actually happening when you do so. You will also learn how to use data APIs so you can take advantage of freely accessible data in your applications, including photo results, news articles and up-to-date data about the world around us.

Self Paced
Self-Paced