Data Structures and Algorithms Nanodegree nd256 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 File size: 2.15 GB

Data Structures and Algorithms Nanodegree nd256 v2.0.0

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.

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4 months to complete
Prerequisite Knowledge

Python & Basic Algebra.See detailed requirements.

Welcome

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.
Unscramble computer science problems
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.
Show me the data structures
Basic Algorithms

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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.
Problems vs. Algorithms
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.
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