Algorithm Design and Analysis | Stanford University

Tim Roughgarden

Gain a deep understanding of algorithm design and analysis techniques with this course taught by renowned expert Prof. Tim Roughgarden at Stanford University.

University CoursesAlgorithmData Structures

Introduction

Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic analysis; divide-and-conquer algorithms and recurrences; greedy algorithms; data structures; dynamic programming; graph algorithms; and randomized algorithms.

screenshot

Highlights

  • Covers a wide range of algorithm design and analysis techniques
  • Taught by Professor Tim Roughgarden, a renowned expert in algorithms
  • Uses the textbook "Algorithm Design" by Kleinberg and Tardos
  • Assumes prerequisite knowledge in discrete mathematics and probability

Recommendation

This course is recommended for students who want to gain a deep understanding of algorithm design and analysis. It is suitable for those with a strong background in computer science and mathematics, and who are interested in developing advanced problem-solving skills.

How GetVM Works

Learn by Doing from Your Browser Sidebar

Access from Browser Sidebar

Access from Browser Sidebar

Simply install the browser extension and click to launch GetVM directly from your sidebar.

Select Your Playground

Select Your Playground

Choose your OS, IDE, or app from our playground library and launch it instantly.

Learn and Practice Side-by-Side

Learn and Practice Side-by-Side

Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.

Explore Similar Hands-on Tutorials

A Field Guide To Genetic Programming

30
Technical TutorialsAlgorithm
Comprehensive guide to genetic programming, covering evolutionary algorithms, computational biology, and advanced programming techniques. Valuable resource for computer scientists, biologists, and researchers.

Algorithms | Fundamental Concepts & Techniques

19
Technical TutorialsAlgorithmData Structures
Comprehensive guide to the fundamental concepts and techniques in the field of algorithms, covering discrete mathematics, data structures, and algorithm analysis.

Algorithms and Data Structures - With Applications to Graphics and Geometry

27
Technical TutorialsAlgorithmData Structures
Explore algorithms, data structures, and their practical applications in graphics and geometry. Suitable for beginners and experienced learners.

Data Structures | Algorithms | Efficient Software Systems

16
Technical TutorialsAlgorithmData Structures
Comprehensive guide to data structures and algorithms, covering arrays, linked lists, stacks, queues, trees, and more. Ideal for students, developers, and professionals seeking to build efficient software systems.

Data Structures (Into Java)

9
Technical TutorialsAlgorithmData StructuresJava
Comprehensive guide to understanding and implementing data structures using Java, covering arrays, linked lists, stacks, queues, trees, and more.

Data Structures and Algorithm Analysis in C++

7
Technical TutorialsAlgorithmC++
Comprehensive guide to data structures, algorithms, and problem-solving using C++. Suitable for students and professionals interested in algorithmic problem-solving.

Elementary Algorithms | Fundamental Algorithms and Data Structures

27
Technical TutorialsAlgorithmData Structures
Comprehensive introduction to fundamental algorithms and data structures, including sorting, searching, and algorithm design. Suitable for beginners and professionals.

Essential Algorithms | Comprehensive Guide to Algorithms and Data Structures

25
Technical TutorialsAlgorithmData Structures
Enhance your programming and problem-solving skills with Essential Algorithms, a comprehensive guide covering essential concepts for beginners and advanced programmers.

Learning Algorithm | Algorithms, Data Structures, Problem-Solving

26
Technical TutorialsAlgorithmData Structures
Explore a wide range of algorithms, from fundamental data structures to advanced techniques like dynamic programming and graph algorithms. Gain practical knowledge for software engineering and problem-solving.