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!...

Apr 06, 2018

Data Structures was really interesting over all, also assignments are quite challenging. It's important to consult the external references & discussion forums if you want to get the best of it.

Sep 19, 2019

The best data structures course that I have taken!\n\nThe complex topics are made simpler at the expense of teaching style that allowed me to make it applicable in a real world situations.

篩選依據：

創建者 Kanak S

•May 15, 2017

Nice course

創建者 Chaobin Y

•Apr 03, 2017

Nice course

創建者 朱慧展

•Jan 19, 2017

nice course

創建者 Unicorn

•Jun 13, 2016

Pretty Nice

創建者 Duchstf

•Aug 16, 2018

Excellent!

創建者 Virginia R A

•Aug 22, 2016

Excellent!

創建者 Mohammed B

•Apr 24, 2019

very good

創建者 Kirill Z

•Sep 18, 2016

very nice

創建者 Lee B U

•Feb 02, 2020

매우 좋습니다.

創建者 Shevelev R R

•Sep 21, 2019

Great@!

創建者 Piyush M

•Jun 10, 2019

Awesome

創建者 Rakesh R

•Aug 21, 2017

love it

創建者 Aakar R

•Aug 06, 2016

awesome

創建者 surajit d

•Jun 26, 2016

Awesome

創建者 Ujjawal K

•Jan 14, 2019

Great.

創建者 刘从从

•Mar 14, 2018

难度太大了

創建者 Sonu M

•Feb 18, 2019

good

創建者 Lie C

•Jun 19, 2018

good

創建者 하림 이

•Oct 31, 2017

good

創建者 JeongEuiDong

•Oct 30, 2017

good

創建者 Harshit S

•Aug 27, 2017

The course covered important data structures and gave an insight on how to counter challenging algorithmic problem through step by step analysis from a very simple approach through slowly and steadily approaching towards better performing algorithms .This gradual rise from a learner's perspective is priceless and helps in better proficiency of the topic.Week 1 taught us basic data structures such as arrays,linked list,stacks and queues and there applications while solving problems on network processing through representing the packets in the form of queues , proper parenthesization of algebraic expressions through an application of stack and representation of tree upside down which we see everywhere in computer science as well as finding the height of a n-ary tree.Week 2 represented very common data structure used in almost any production system's source code the Array List and its time analysis through a new method called amortized time which was analyzed through banker's method,physicist method and the aggregate method .Week 3 described some pretty fast data structures whose mere usage can increase performance considerably such as priority queues whose representation are binary heaps and have special characteristics of Sifting up and Sifting down to maintain the classic heap property and it introduces a very fast sorting algorithm called heap sort.And this was not it another data structure was introduced which is called the disjoint set ( Union find) which made finding paths in very large graphical systems just a formality.The best part of this data structure remained integral to the characteristic of the course to find the efficient solution gradually but definitely as it showed which finding the union find function first through representing as arrays and assigning the parents as indexes and slowly finding the problem in arrays to go through tree representation as a necessity not just because every one has done it.Then came the fourth week and a learner's performance seeking mindset was in full throttle whether it be hash tables,hash functions or distributed hash tables used by Google Drive, Yandex Disk or Drop box there was no way stopping it and thus whole week showed how much can be achieved through hash table representation of data on which these companies integral technologies are based on.On a personal note I also saw the representation of distributed hash tables in Akamai's cloud distributed networks.The week 5 dig deeper into Binary Search Trees and there representation as well as there height were subject to scrutiny with the several applications such as AVL trees as well as Splay Trees all showed certain characteristics of height balancing which are very useful in caching and thus were considered as assignment to have a look and feel of big classes and using methods such as merge and split to get fast retrieval.Thus performance oriented mind set was explored to the fullest through playing of these data structure and applying them on real life scenarios.

創建者 Jenna W

•Sep 17, 2016

A really great course, you should definitely take this second after Algorithmic Toolbox, as that has an easier learning curve for the very 'CS professor' style code (lots of single letter variables and other quirks) and how projects should be submitted and tested.

That said, there is a lot of good learning in this course. Make sure you have some good Algorithms textbooks to accompany the lectures, they have recommendations in the course. I personally use Sedgewick's book and CLRS which aren't exactly what they suggest, but work well. Take your time with the learning, make sure you really understand the concepts before moving on to the homework. Use multiple sources to learn (they provide plenty of links!) and you'll do well.

In response to a very politely asked request for clarity: I rated this 4/5 rather than 5/5 stars as I found that for my preferred language (Python) some of the starter files were very poorly created. This meant I often have to rewrite the initial parsing of the inputs because it would create variables that contained incorrect or incomplete input data. Further, there were some non-harmful quirks like semi-colons or parameters shadowing Python reserved words in the code. The next course in this series, Algorithms on Graphs, did not seem to have any of these issues, though!

創建者 Christopher W

•Mar 08, 2020

A really good course. I'd have to say the beginning lectures went pretty darn fast. If I hadn't had previous exposure to data structures, I'm sure I would have felt totally buried. As it is it served as a great refresher for the basics, and then the more advanced concepts later were well-presented and thoroughly analyzed. I have a good feel for the use and running times of the operations discussed. I felt bad that I didn't do all the programming exercises when only like 2 or 3 were needed to pass. They were pretty challenging, and by the time I had done enough to pass I was like, OK moving on....maybe I'll circle back to the ones I didn't get to.

創建者 Adrian H

•Sep 28, 2016

The final module with the Splay tree is way too difficult when compared to the rest of the material in the course. This course would be better structured with three assignments as follows: 1) tree order problem, 2) a simpler tree assignment that only deals with a basic binary search tree, 3) the set range sum problem implementing the splay tree, as an advanced problem. Aside from the difficulty of the last module, this is a great course. It's very comprehensive and you'll take away lots of useful information on course completion.

創建者 Miguel R

•Sep 02, 2016

Excellent course in general, and I learned a lot of new data structures that one doesn't generally learn about in standard algorithms and data structures courses, like disjoint sets and splay trees.

Only complaint is that sometimes the problems are too complicated for how easy they are. By this I mean that the problem statement is very long and elaborate, when what they are really asking is something trivial that can be programmed in a few lines, but it takes a while to understand just what they are asking.