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Data Structures

This course is a part of Data Structures and Algorithms, a 6-course Specialization series from Coursera.

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! Do you have technical problems? Write to us: [email protected]

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University of California San Diego

Rating 4.5 based on 234 ratings
Length 7 weeks
Effort 4 weeks of study, 5-10 hours/week
Starts Nov 11 (5 weeks ago)
Cost $79
From University of California San Diego, National Research University Higher School of Economics via Coursera
Instructors Alexander S. Kulikov, Michael Levin, Daniel M Kane, Neil Rhodes
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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What people are saying

According to other learners, here's what you need to know

data structure in 41 reviews

This is a great course to learn Data Structures.

Really great lectures and test Really good course to understand implementation details and analysis of the most used data structures, both basic and advanced.

great things to learn about data structures Course has a slow pace by the time it reaches hashing and the videos only reads out the formulas.

Conteúdo muito completo e a didática é perfeita fantabulous experience Data Structures was really interesting over all, also assignments are quite challenging.

Very succinct summary of data structures with useful problems to get a good grasp of basics!

Got introduced & practiced multiple data structures which was a must for me as I am not a computer science graduate.

Perfect Course very useful Thank you for providing this awesome course This course gives you real world examples of the data structures that you are going to learn and implement and and this really helps in answering the basic question "Why am I doing for what am I doing?".

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splay trees in 11 reviews

It's a pretty big jump in difficulty (I don't think they explained splay trees in the lectures very well; it was pretty fast), but I was so ecstatic when I solved it that I didn't mind.

The problem with the splay trees is probably characteristic.

Course is Excellent.The final week is a bit fast, understanding the splay was very difficult for me.Could have given more examples for splay trees.

As for the problems, they were the main source of learning, but were also at times a bit frustrating (the splay trees starter code was rather sad to look at).

The only frustrating thing was Week 6's programming assignment, where the advanced problems were hard, and so I think there should've been more elaborate coverage of splay trees so that students could understand them better.

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very good course in 9 reviews

Very good course, only problem is the little help offered by mentors in the discussion forum I learned a lot many subtitle of the video doesn't match what the speaker is saying, so I hope you can improve it,thx Perhaps the videos on AVL Trees (Rotations basically) and Splay Trees can be enhanced to give a more thorough grounding.

Very good course for data structures, especially the assignments and the auto-grader.

Very good course Wow.

This is a very good course.

A very good course that is suitable to young student The quality of the course is very high.

Very good course.

awesome A very good course if you want to learn how we organize data in such a way that we can perform specific operations with low computing cost.

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algorithmic toolbox in 9 reviews

Continues with the rigor and learning approach from the previous course, Algorithmic Toolbox, and builds upon it.

Interesting, challenging and just like the algorithmic toolbox course a FANTASTIC way to practise implementing solutions in a programming language of your choice.

I learned many things this course is more difficult than algorithmic toolbox but when you work hard you can finish all units in the beginning i thought that i would not be able to continue because i dont have a lot of knowledge in c+, java or python, but i decided to learn c+ sonce the first course.

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.

[Slightly updated according to Michael's questions]The course is fine, but comparing to the previous one - Algorithmic Toolbox - this one is weaker and with lesser quality.

These courses are the really good base, after which you can open the books related to algorithms and read more details if you needed.I am definitely going to complete the whole specialization!The only thing which was not convenient for me is that both courses Algorithmic Toolbox and Data Structures are started at the same time.

Also, the testing techniques presented here are indispensable in the real life, and many learners of the Algorithmic Toolbox course have already confirmed thisHello Mr. Levin,First please forgive me for communicating with you in this place.

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last two weeks in 7 reviews

The last two weeks are all about balanced BSTs and there's only one assignment (with three problems) covering them which has stated expected time for completion 25 hours.

Another good course, though the last two weeks were a lot harder to follow than the prior ones.

The last two weeks on AVL and Splay trees need more examples and felt a bit rushed.

Glad I took it :) Recommended.Although, I do recommend some more material on the last two weeks - I loved the concepts that were taught, but I feel there could have been more lectures on BST applications, given how powerful they are!

The last two weeks felt rushed.

best course for algorithm The last two weeks' content may need to be revised to provide a better learning experience.

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last week in 6 reviews

About „desperately hard“ last week assignment: I don't agree with this comment.

The last week gets hard but its as rewarding as challenging.

Although, the programming assignment for the last week could be better.

Maybe its because of difficulty of the last weeks topics.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Structures/Bridge $81k

Structures Technician 1 $81k

Associate Structures Engineering $83k

Structures Designer $85k

Structures CADD $91k

Structures Mech $94k

Aircraft Structures $96k

Structures Foreman $98k

Engineer of Structures $100k

Structures Engineer 1 2 $103k

Product Engineer - Structures $115k

Structures Estimator Manager $127k

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Coursera

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University of California San Diego

Rating 4.5 based on 234 ratings
Length 7 weeks
Effort 4 weeks of study, 5-10 hours/week
Starts Nov 11 (5 weeks ago)
Cost $79
From University of California San Diego, National Research University Higher School of Economics via Coursera
Instructors Alexander S. Kulikov, Michael Levin, Daniel M Kane, Neil Rhodes
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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