MicroMasters® Program in Algorithms and Data Structures

University of California

via

edX

Course Features

Duration

9 months

Delivery Method

Online

Available on

Limited Access

Accessibility

Desktop, Laptop

Language

English

Subtitles

English

Level

Advanced

Effort

10 hours per week

Teaching Type

Self Paced

Course Description

MicroMasters is a combination of theory and practice. You will learn algorithms for solving different computational problems by implementing more than 100 algorithmic coding challenges in the programming language of your choosing.

You won't find an Algorithms online course that offers the same level of programming challenges you will face in your next job interview. We have spent thousands of hours creating challenges to prepare you for the many programming questions you will face at your next job interview. Learning through application is what we believe in, especially when it involves learning algorithms.

We have created multiple tests for each algorithm that you create and implement. Although it may seem difficult, we believe that this is the best way to understand the algorithm and master programming.

Course Overview

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Understand essential algorithmic techniques and apply them to solve algorithmic problems

Implement programs that work in less than one second even on massive datasets

Test and debug your code even without knowing the input on which it fails

Formulate real life computational problems as rigorous algorithmic problems

Prove correctness of an algorithm and analyze its running time

Course Content

Expand all sections

Module 1: Algorithmic Design and Techniques

Module 2: Data Structures Fundamentals

Module 3: Graph Algorithms

Module 4: NP-Complete Problems

Course Instructors

Pavel Pevzner

Ronald R. Taylor Professor of Computer Science

Pavel Pevzner is Ronald R. Taylor Professor of Computer Science at the University of California, San Diego. He holds a Ph.D. from Moscow Institute of Physics and Technology, Russia. He is a Howard Hu...

Daniel Kane

Assistant Professor, Computer Science and Engineering & Dept. of Mathematics

Daniel is an assistant professor at UCSD with a joint appointment between the Department of Computer Science and Engineering and the Department of Mathematics. He holds B.S. from MIT and Ph.D. from Harvard.

Alexander S. Kulikov

Visiting Professor

Alexander is a research fellow at Steklov Mathematical Institute at St. Petersburg, Russia and a visiting professor at University of California, San Diego. He have been teaching algorithms classes for more than eight years.

Michael Levin

Chief Data Scientist

Michael serves as chief data scientist at Yandex.Market (Yandex is the leading Internet company in Russia, and Yandex.Market is the leading service for price comparison online shopping in Russia). He...