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  1. Home
  2. Learning Paths

Data Science Foundations: Data Structures and Algorithms Learning Path

Data Science Foundations: Data Structures and Algorithms is a Specialization designed by Coursera. It consists of three courses and can be completed in three months with 9 hours of learning content .

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Description

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 course will teach the fundamentals of data structures and algorithms with a focus on data science applications. This specialization 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. We 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.

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Free Learning Paths by Career Track

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Included Courses

Coursera
University of Colorado Boulder
Free
1. Algorithms for Searching, Sorting, and Indexing
Sriram Sankaranarayanan

34 hours

Intermediate

7,761
Jupyter Python Algorithms Applied Mathematics Arrays Data Analysis Data Science
Coursera
University of Colorado Boulder
Free
2. Trees and Graphs: Basics
Sriram Sankaranarayanan

34 hours

Advanced

2,446
Python Algorithms Applied Mathematics Data Analysis Data Science Data Visualization
Coursera
University of Colorado Boulder
Free
3. Dynamic Programming, Greedy Algorithms
Sriram Sankaranarayanan

38 hours

Advanced

2,446
Jupyter Python Algorithms Data Analysis Optimization Programming
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