Coursera | Data Structures [FCO]

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This course is part of the Data Structures and Algorithms Specialization

ourse 1 of 1 in the

Data Structures and Algorithms Specialization
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Intermediate Level

Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala.

English

Subtitles: English
Offered By

UNIVERSITY OF CALIFORNIA SAN DIEGO
NATIONAL RESEARCH UNIVERSITY HIGHER SCHOOL OF ECONOMICS
About this Course

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A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures. A few examples of questions that we are going to cover in this class are the following: 1. What is a good strategy of resizing a dynamic array? 2. How priority queues are implemented in C++, Java, and Python? 3. How to implement a hash table so that the amortized running time of all operations is O(1) on average? 4. What are good strategies to keep a binary tree balanced? You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space!

Instructors

1. Alexander S. Kulikov

Visiting Professor

Department of Computer Science and Engineering

2. Michael Levin

Lecturer

Computer Science

3. Daniel M Kane

Assistant Professor

Department of Computer Science and Engineering / Department of Mathematics

4. Neil Rhodes

Adjunct Faculty

Computer Science and Engineering

About the Data Structures and Algorithms Specialization

This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it comes to learning algorithms…or anything else in computer science! For each algorithm you develop and implement, we designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming. The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco (1000 times faster than the standard shortest path algorithms!) Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.