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Foundations of Data Structures and Algorithms Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
6 months
Duration
6 months
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

This Foundations of Data Structures and Algorithms Specialization offered by Coursera in partnership with University of Colorado Boulder will teach the fundamentals of data structures and algorithms with a focus on data science applications.

Overview

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing.

This Foundations of Data Structures and Algorithms Specialization offered by Coursera in partnership with University of Colorado Boulder is targeted towards learners who are broadly interested in programming applications that process large amounts of data (expertise in data science is not required), and are familiar with the basics of programming in python.

Key facts

  • You will learn about various data structures including arrays, hash-tables, heaps, trees and graphs along with algorithms including sorting, searching, traversal and shortest path algorithms. 
  • This specialization can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. 
  • These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals.

What You Will Learn:

  • Organize, store and process data efficiently using sophisticated data structures and algorithms
  • Create applications that are supported by highly efficient algorithms and data structures for the task at hand
  • Design algorithms and analyze their complexity in terms of running time and space usage

Skills You Will Learn:

  • Algorithms
  • Theoretical Computer Science
  • Data Structures
  • Graph Theory
  • Computer Programming
  • Problem Solving
  • Mathematical Theory & Analysis
  • Mathematics
  • Python Programming

Programme Structure

Courses include:

  • Algorithms for Searching, Sorting, and Indexing
  • Trees and Graphs: Basics
  • Dynamic Programming, Greedy Algorithms
  • Approximation Algorithms and Linear Programming
  • Advanced Data Structures, RSA and Quantum Algorithms

Key information

Duration

  • Part-time
    • 6 months
    • Flexible

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Advanced level

  • Recommended experience: Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. 
  • Some programming experience with Python

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • Coursera Plus: Subscribe to build job-ready skills from world-class institutions.
  • $59/month, cancel anytime or $399/year with 14-day money-back guarantee

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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