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Udacity | Data Structures And Algorithms Nanodegree v2.0.0 [FCO]
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Udacity - Data Structures And Algorithms Nanodegree v2.0.0 [FCO]

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

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.

Advanced Algorithms
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  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
Course Source: https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256

NOTE: Each folder, zipped due to the files count and large filenames to avoid torrent creation errors, contains all material

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About Content.txt237 B
Assets.zip1.43 MiB
Part 01-Module 01-Lesson 01_Introduction.zip3.87 MiB
Part 01-Module 01-Lesson 02_Python Refresher.zip3.29 MiB
Part 01-Module 01-Lesson 03_How to Solve Problems.zip271.07 MiB
Part 01-Module 01-Lesson 04_Efficiency.zip33.8 MiB
Part 01-Module 01-Lesson 05_Unscramble Computer Science Problems.zip10.21 KiB
Part 02-Module 01-Lesson 01_Arrays and Linked Lists.zip44.92 MiB
Part 02-Module 01-Lesson 02_Stacks and Queues.zip47.4 MiB
Part 02-Module 01-Lesson 03_Recursion.zip29.98 MiB
Part 02-Module 01-Lesson 04_Trees.zip196.99 MiB
Part 02-Module 01-Lesson 05_Maps and Hashing.zip35.74 MiB
Part 02-Module 01-Lesson 06_Show Me the Data Structures.zip52.91 KiB
Part 03-Module 01-Lesson 01_Basic Algorithms.zip64.98 MiB
Part 03-Module 01-Lesson 02_Sorting Algorithms.zip76.28 MiB
Part 03-Module 01-Lesson 03_Faster Divide Conquer Algorithms.zip81.56 MiB
Part 03-Module 01-Lesson 04_Problems vs. Algorithms.zip46.15 KiB
Part 04-Module 01-Lesson 01_Greedy Algorithms.zip8.62 KiB
Part 04-Module 01-Lesson 02_Graph Algorithms.zip49.48 MiB
Part 04-Module 01-Lesson 03_Dynamic Programming.zip22.13 MiB
Part 04-Module 01-Lesson 04_A.zip66.34 MiB
Part 04-Module 01-Lesson 05_Route Planner.zip3.78 MiB
Part 05-Module 01-Lesson 01_Why Python Programming.zip9.08 MiB
Part 05-Module 01-Lesson 02_Data Types and Operators.zip178.09 MiB
Part 05-Module 01-Lesson 03_Data Structures.zip61.43 MiB
Part 05-Module 01-Lesson 04_Control Flow.zip173.98 MiB
Part 05-Module 01-Lesson 05_Functions.zip66.74 MiB
Part 05-Module 01-Lesson 06_Scripting.zip101.18 MiB
Part 05-Module 01-Lesson 07_Advanced Topics.rar18.89 MiB
Part 06-Module 01-Lesson 01_Industry Research.zip1005.57 KiB
Part 06-Module 01-Lesson 02_Take 30 Min to Improve your LinkedIn.zip92.85 MiB
Part 06-Module 01-Lesson 03_Optimize Your GitHub Profile.zip108.92 MiB
Part 07-Module 01-Lesson 01_Technical Interview - Python.zip320.33 MiB
Table of Content.html103.51 KiB