Algorithms for Big Data | IIT Madras Course

IIT Madras

Explore fundamental algorithmic techniques and data structures for processing large-scale datasets, including MapReduce, streaming algorithms, and sketching techniques.

University CoursesMachine Learning

Introduction

This course provides an introduction to the design and analysis of algorithms for big data. It covers fundamental algorithmic techniques and data structures for processing large-scale datasets, including MapReduce, streaming algorithms, and sketching techniques.

Highlights

  • Covers fundamental algorithmic techniques and data structures for processing large-scale datasets
  • Includes topics such as MapReduce, streaming algorithms, and sketching techniques
  • Taught by faculty from the prestigious Indian Institute of Technology Madras

Recommendation

This course is recommended for students and professionals interested in learning about algorithms and data structures for big data processing. It provides a solid foundation in the design and analysis of efficient algorithms for large-scale data problems.

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

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 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.

Linked List Problems | Data Structures | Programming Algorithms

8
Technical TutorialsAlgorithmData Structures
Explore a wide range of linked list problems, develop visualization skills, and enhance your problem-solving abilities for coding interviews and exams.

Matters Computational: Ideas, Algorithms, Source Code

9
Technical TutorialsAlgorithmProgramming
Comprehensive book covering computational algorithms, source code, and programming concepts. Recommended for programmers and computer scientists.