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Learner Reviews & Feedback for I/O-efficient algorithms by EIT Digital

57 ratings

About the Course

Operations on data become more expensive when the data item is located higher in the memory hierarchy. An operation on data in CPU registers is roughly a million times faster than an operation on a data item that is located in external memory that needs to be fetched first. These data fetches are also called I/O operations and need to be taken into account during the design of an algorithm. The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. We will work with a simplified memory hierarchy, but the notions extend naturally to more realistic models. Prerequisites: In order to successfully take this course, you should already have a basic knowledge of algorithms and mathematics. Here's a short list of what you are supposed to know: - O-notation, Ω-notation, Θ-notation; how to analyze algorithms - Basic calculus: manipulating summations, solving recurrences, working with logarithms, etc. - Basic probability theory: events, probability distributions, random variables, expected values etc. - Basic data structures: linked lists, stacks, queues, heaps - (Balanced) binary search trees - Basic sorting algorithms, for example MergeSort, InsertionSort, QuickSort - Graph terminology, representations of graphs (adjacency lists and adjacency matrix), basic graph algorithms (BFS, DFS, topological sort, shortest paths) The material for this course is based on the course notes that can be found under the resources tab. We will not cover everything from the course notes. The course notes are there both for students who did not fully understand the lectures as well as for students who would like to dive deeper into the topics. The video lectures contain a few very minor mistakes. A list of these mistakes can be found under resources. If you think you found an error, report a problem by clicking the square flag at the bottom of the lecture or quiz where you found the error....

Top reviews


Nov 5, 2019

Everything was clearly explained and the questions were quite intuitive and checking my knowledge. More examples for different scenarios too would help us a lot to learn more.


Feb 28, 2022

The excercises and assignments helped in undertanding the concepts much better. Also as this course content can't be found easily at one place this really helped. Thank you

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1 - 13 of 13 Reviews for I/O-efficient algorithms

By Nicholas P

Jun 25, 2020

Great introduction the I/O-centric model of computation. The course was fairly easy to follow but the quizzes were a bit confusing at times. There's also not much support going around in the discussion boards. Nevertheless, the material is easily self-teachable and you'll come out of the course knowing a couple more tools and tricks than you started with.

By Natarajan C

Nov 6, 2019

Everything was clearly explained and the questions were quite intuitive and checking my knowledge. More examples for different scenarios too would help us a lot to learn more.


May 9, 2022

The course is really good and the course material is also amazing. I highly reccomend it provided you have an interest in this specialization.

By Yucheng Z

Sep 29, 2020

Really like the course. Though it's difficult and challenging, I managed to understand the concept. I will keep practicing.

By Jörg S

Aug 22, 2022

Good learning materials but at same places too theoretical (in my opinion).

By 周柏宇

Jan 31, 2020

An introduction to the I\O-efficient algorithms. Short and sweet!

By vignesh p

Jul 3, 2020

Very precise and efficient course.

By Sergio G

Apr 27, 2020


Thanks for the tuition


Jul 6, 2022


By Kota V K 1

May 27, 2021


By Никулин О А

Aug 30, 2020

Great course, but interface is quit lacking, because course notes are under different section

By Sinha A

Aug 25, 2020

The evaluations should have been more in number.

By Raghu V

Dec 1, 2021

The course touched on critical theoretical concepts around I/O efficiency while designing algorithms but I felt the resource notes lacked depth and clarity (they had overlap with the video lessons). Would have been good to get insight into solutions for exercises (at least on the course notes)