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Home » Ebooks & Tutorials » Technical » Development Training » Foundations of Data Structures and Algorithms Specialization | Coursera

Foundations of Data Structures and Algorithms Specialization | Coursera

04/06/2024 Tut4DL Leave a Comment


Foundations of Data Structures and Algorithms Specialization | Coursera [Update 01/2024]
English | Size: 15.37 GB
Genre: eLearning

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

Specialization – 5 course series
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.

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.

Applied Learning Project

Learners will solve data-structure problems by analyzing and designing algorithms for searching, sorting, and indexing; creating trees and graphs; and addressing intractability. Courses also include conceptual algorithm design problems as well as
opportunities to program data-structures/algorithms in the python
programming language.

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