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Michael Littman

Take Udacity's free Intro to Algorithms course and get an introduction to the design and analysis of algorithms. Learn how to analyze networks and discover how individuals are connected.

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What's inside

Syllabus

A Social Network Magic Trick
Problem Set 1
Growth Rates in Social Networks
Problem Set 2
Read more
Problem Set 2 Solutions
Basic Graph Algorithms
Problem Set 3
Problem Set 3 Solutions
It's Who You Know
Problem Set 4
Problem Set 4 Solutions
Strong and Weak Bonds
Problem Set 5
Hardness of Network Problems
Problem Set 6
Lesson 7
Final Assessment
Extra Challenge Problems

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Introduces fundamentals of algorithms and networks
No prerequisites explicitly required
Content features basic graph algorithms and analysis
Taught by Michael Littman, a recognized expert in the field
Focus is primarily on analysis of networks

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Reviews summary

Algorithms, but not intro

For beginners, this course may be challenging. It doesn't assume you're starting from scratch. You need a strong grasp of programming as well as an understanding of Algebra II level math. Some reviewers found the course to be too fast-paced with unclear explanations.
Not beginner-friendly
"It really feels like an algorithms refresher course. This is not a good course for beginners."
Assumes high-level math
"Not much of an intro - he goes way too fast & you need a LOT MORE than high school algebra for this!"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Intro to Algorithms with these activities:
Review Linear Algebra Concepts
Prepare for success by reviewing fundamental linear algebra concepts that will be utilized in the course.
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  • Review basic matrix operations
  • Recall properties of vector spaces
  • Practice solving systems of linear equations
Kaggle Tutorial on Social Network Analysis
Learn about social network analysis techniques through a practical Kaggle tutorial.
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  • Create a Kaggle account
  • Complete the Kaggle tutorial on social network analysis
Analyze Social Networks Using NetworkX
Gain hands-on experience in analyzing social networks by working with NetworkX.
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  • Install NetworkX
  • Load and visualize social network data
  • Calculate network metrics
  • Generate and analyze Erdős–Rényi graphs
Five other activities
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Show all eight activities
Implement Graph Traversal Algorithms
Solidify understanding of graph traversal algorithms by implementing them in a coding environment.
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  • Review the basics of graph traversal
  • Implement depth-first search
  • Implement breadth-first search
  • Apply the algorithms to sample graphs
  • Debug and refine implementation
Join an Online Study Group for the Course
Enhance understanding of course material through discussions and collaboration with peers.
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  • Identify or create an online study group
  • Schedule regular meetings
  • Review course material together
  • Discuss assignments and projects
Read Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Analyze networks and learn about the underlying structures of social systems by reading a foundational text in the field.
Show steps
  • Preview the introduction and chapter summaries
  • Read each chapter carefully
  • Summarize the book in your own words
Develop a Social Network Data Visualization
Deepen understanding of data visualization by creating visual representations of social network data.
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Show steps
  • Gather social network data
  • Select appropriate visualization methods
  • Create static and interactive data visualizations
  • Critique and refine visualizations
Design a Social Network Analysis Project
Develop a research proposal for a social network analysis project based on the concepts learned in the course.
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Show steps
  • Identify a research question
  • Review relevant literature
  • Design data collection methods
  • Develop a data analysis plan

Career center

Learners who complete Intro to Algorithms will develop knowledge and skills that may be useful to these careers:
Network Analyst
Network Analysts use their understanding of network structures and algorithms to solve business problems and to optimize the performance of a company's networks. Udacity's Intro to Algorithms course is an excellent starting point for building this foundation.
Data Analyst
Data Analysts play a vital role in helping businesses understand and use their data. The algorithms covered in Udacity's Intro to Algorithms course will provide Data Analysts with the ability to extract and analyze data more effectively.
Software Engineer
Software Engineers who specialize in designing and optimizing software algorithms may find the content in the Udacity Intro to Algorithms course to be extremely valuable. This course will help Engineers to improve their ability to analyze and design algorithms, which will lead to more efficient and effective software.
Algorithm Engineer
For Algorithm Engineers, the Udacity Intro to Algorithms course can be extremely useful. This course provides a solid introduction to the theory and practice of algorithms, which are essential for Algorithm Engineers.
Data Scientist
Data Scientists who are tasked with developing and implementing algorithms will benefit from the knowledge provided in Udacity's Intro to Algorithms course. This course will provide Data Scientists with a deeper understanding of the fundamental principles of algorithms and their implementation.
Quantitative Analyst
The coursework in Udacity's Intro to Algorithms can be a useful introduction for those who are interested in becoming Quantitative Analysts. This course provides an overview of the fundamental concepts of algorithms, which are essential for success as a Quantitative Analyst.
Research Scientist
The Udacity Intro to Algorithms course provides a solid introduction to the design and analysis of algorithms. This knowledge is essential for Research Scientists who are working on developing new algorithms and improving existing ones.
Product Manager
Udacity's Intro to Algorithms course can be helpful for Product Managers who are working on developing new products or features that rely on algorithms. This course will provide these Product Managers with a foundational understanding of how algorithms work, which will enable them to make better decisions about how to use algorithms in their products.
Business Analyst
While the Udacity Intro to Algorithms course is not directly related to the field of Business Analysis, it may be helpful for Business Analysts who are interested in gaining a better understanding of how algorithms are used in business. This course will provide these Business Analysts with a solid foundation in the fundamentals of algorithms, which will allow them to better understand and communicate with technical teams.
Project Manager
The Udacity Intro to Algorithms course may be helpful for Project Managers who are working on projects that involve the development or use of algorithms. This course will provide these Project Managers with a basic understanding of how algorithms work, which will enable them to better manage and communicate with technical teams.
Software Developer
The Udacity Intro to Algorithms course may be helpful for Software Developers who are interested in learning more about the design and implementation of algorithms. This course will provide these Developers with a solid foundation in the fundamentals of algorithms, which will enable them to write more efficient and effective code.
Database Administrator
The Udacity Intro to Algorithms course may be helpful for Database Administrators who are interested in learning more about how algorithms are used to optimize database performance. This course will provide these Database Administrators with a solid foundation in the fundamentals of algorithms, which will enable them to better understand and tune database algorithms.
Technical Writer
The Udacity Intro to Algorithms course may be helpful for Technical Writers who are interested in learning more about the technical aspects of computer science. This course will provide these Technical Writers with a solid foundation in the fundamentals of algorithms, which will enable them to better understand and communicate with technical teams.
Computer Scientist
The Udacity Intro to Algorithms course may be helpful for Computer Scientists who are interested in learning more about the design and analysis of algorithms. This course will provide these Computer Scientists with a solid foundation in the fundamentals of algorithms, which will enable them to conduct research and development in this field.
Bioinformatician
The Udacity Intro to Algorithms course may be helpful for Bioinformatics who are interested in learning more about the algorithms used in the analysis of biological data. This course will provide these Bioinformatics with a solid foundation in the fundamentals of algorithms, which will enable them to better understand and develop algorithms for the analysis of biological data.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Intro to Algorithms.
This established text on algorithms will be of great use in getting a firm grounding in the field, in Ukrainian.
Will be a supplemental text for the course on algorithms, and adds a broad historical context to the subject.
This established text on algorithms will be of great use in getting a firm grounding in the field, in Spanish.
This reference gathers together materials in the field of algorithms in one volume. It could be used as a supplement to the course to deepen knowledge already gained.
This textbook covers the field of designing algorithms, and commonly used reference in the field.
An undergraduate textbook that explores the field of algorithms, this book would assist the learner in the foundational material to begin the study of algorithms.
A standard textbook on Algorithms. It is commonly used as a supplemental text, and is recommended as additional reading.

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