About this course: 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!
Who is this class for: Programmers with basic experience looking to understand the practical and conceptual underpinnings of algorithms, with the goal of becoming more effective software engineers. Computer science students and researchers as well as interdisciplinary students (studying electrical engineering, mathematics, bioinformatics, etc.) aiming to get more profound understanding of algorithms and hands-on experience implementing them and applying for real-world problems. Applicants who want to prepare for an interview in a high-tech company.
Taught by: Alexander S. Kulikov, Visiting Professor
Department of Computer Science and Engineering
Taught by: Michael Levin, Lecturer
Computer Science
Taught by: Daniel M Kane, Assistant Professor
Department of Computer Science and Engineering / Department of Mathematics
Taught by: Neil Rhodes, Adjunct Faculty
Computer Science and Engineering
| Basic Info |
Course 2 of 6 in the
Data Structures and Algorithms Specialization.
|
| Level | Intermediate |
| Commitment | 4 weeks of study, 5-10 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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Thanks for the great course! Giving it a five stars. Although, the programming assignment for the last week could be better. Instead of implementing the same in-order tree-traversing three times with minor variations (first time as requested, second time to test if a given tree is a BST, and a "hard BST" variance), would be better to include tasks on implementing balancing and splaying a tree.
Course is well designed and an enjoying challenge. It's a bedrock course for anyone solving computational problems.
it's a good course overall.
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nice explained course