Event Details

Are you a software developer with a burning desire to dive deep into Computer Science topics?

Want to acquire a solid grasp of Data Structures and Algorithms (DSA) to strengthen your technical skills or to help prepare for interviews?

If so, this is the course for you!

Professors.io is proud to offer our first semester long course on Data Structures and Algorithms- taught by an Arizona State University lecturer and CS Ph.D. student.




About the Course:

The course will cover material found in a standard Undergraduate DSA course. Major topics include:

  • Foundations: algorithms, asymptotics, algorithm analysis.

  • Design and Analysis techniques: divide and conquer, greedy algorithms, dynamic programming.

  • Data Structures: hash tables, red-black trees and their variants.

  • Graph algorithms: searching, minimum spanning trees, shortest paths.

  • Randomized algorithms: Chernoff bounds, probabilistic analysis.

  • Intractability: NP-completeness and related classes, reductions.


For complete course details, you can find the syllabus here.




Prerequisites:

Programming experience and mathematical maturity. This includes familiarity with functions, relations, sets, and proofs.




Meet Your Instructor: Ryan Dougherty


Ryan Dougherty is a Ph.D. student in Computer Science at Arizona State University. His research concerns combinatorial objects and their applications, which include software and hardware testing, derandomization of probabilistic algorithms, and combinatorial designs.




Schedule:

July 10th - October 18th

Every Tuesday & Thursday, from 6:00pm – 7:15pm.

Please note that class will not be held the week of October 8th.




Questions:

If you have any questions, please don't hesitate to email [email protected]




Refund Policy:

Life happens- you shouldn't have to pay for a course you don't take.

We'll happily refund your purchase if you cancel before the end of the second course week (07/19).

  • When: Wednesday, Jul. 11 - 1:00 am
    to
    Friday, Oct. 19 2:15 am

  • Web: Visit Website