# [Udacity] Data Structures And Algorithms Nanodegree v2.0.0

Udacity – Data Structures And Algorithms Nanodegree v2.0.0

Nanodegree Program

Get hands-on practice with over 100 data structures and algorithm exercises and technical mentor support when needed to help prepare you for interviews and on-the-job scenarios.

Data Structures & Algorithms

[Udacity] Data Structures And Algorithms Nanodegree v2.0.0 In this course you will learn data structures and algorithms by solving 80+ practice problems. You will begin each course by learning to solve defined problems related to a particular data structure and algorithm. By the end of each course, you would be able to evaluate and assess different data structures and algorithms for any open-ended problem and implement a solution based on your design choices.

Prerequisite knowledge

– Intermediate Python programming knowledge
– Basic algebra knowledge

Course Content:

Introduction
Get an overview of your program. Meet your instructors, and refresh your Python skills. Learn the framework to deconstruct any open-ended problem and then understand the concepts of time and space complexity.

Data Structures
Learn different data structures that can be used to store data. Implement different methods used to manipulate these data structures and examine the efficiency. Understand the advantages and applications of different data structures. Learn how to approach open ended problems (either in interview or real-world) and select appropriate data structures based on requirements.

Basic Algorithms
Learn and implement basic algorithms such as searching and sorting on different data structures and examine the efficiency of these algorithms. Use recursion to implement these algorithms and then learn how some of these algorithms can be implemented without recursion. Practice selecting and modifying these algorithms for a variety of interview problems.

Build on your algorithm skills by learning more advanced algorithms such as brute-force greedy algorithms, graph algorithms, and dynamic programming which optimizes recursion by storing results to sub problems.

Program Details

Program overview: Why should I take this program?

Whether you want to be a web developer, a machine learning engineer, or a data scientist, having a deep understanding of Data Structures and Algorithms is essential to acing job interviews and becoming a successful software engineer. As Linus Torvalds famously said, “Bad programmers worry about the code. Good programmers worry about data structures and their relationships”.

The Data Structures and Algorithms Nanodegree program will help you excel at solving everything from well-defined problems, like how to calculate the efficiency of a specific algorithm, to more open-ended problems, like building your own private blockchain or writing a web-crawler.

You’ll work on over 80 exercises and four real-world projects so that you can get the hands-on practice required to learn how to implement appropriate solutions based on your design choices.

Instructor(s)

Brynn Claypoole, Brynn is a former Udacity employee who worked as Lead Data Analyst at Udacity before joining Facebook as Data Engineer. Currently, she is working as software engineer with 10x Genomics.

Abe Feinberg, Abe is a Content Developer at Udacity and previously taught university courses in psychology and computer science. He loves both learning and teaching, and has a particular passion for breaking down difficult concepts and making them easier to master.

Kyle Stewart-Franz, Kyle has developed projects for a variety of Udacity’s Nanodegree programs, such as Self-Driving Car Engineer, Robotics, and Blockchain. Kyle, a self-taught developer, is always striving towards creating great learning experience for students.

General Info:

Author(s): Brynn Claypoole, Abe Feinberg, Kyle Stewart-Franz
Language: English
Updated: 2022
Videos Duration: 7h 49m
Subtitle: En-US Included
Files In Folders: 1,851 Files, 54 Folders

Size: 2.11 GB

https://www.udacity.com/course/data-structures-and-algorithms-nanodegree–nd256.

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