About this Course
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Intermediate Level


Subtitles: English, Spanish

What you will learn

  • Check

    Essential algorithmic techniques

  • Check

    Design efficient algorithms

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    Practice solving algorithmic interview problems

  • Check

    Implement efficient and reliable solutions

Skills you will gain

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level


Subtitles: English, Spanish

Syllabus - What you will learn from this course

5 hours to complete

Programming Challenges

Welcome to the first module of Data Structures and Algorithms! Here we will provide an overview of where algorithms and data structures are used (hint: everywhere) and walk you through a few sample programming challenges. The programming challenges represent an important (and often the most difficult!) part of this specialization because the only way to fully understand an algorithm is to implement it. Writing correct and efficient programs is hard; please don’t be surprised if they don’t work as you planned—our first programs did not work either! We will help you on your journey through the specialization by showing how to implement your first programming challenges. We will also introduce testing techniques that will help increase your chances of passing assignments on your first attempt. In case your program does not work as intended, we will show how to fix it, even if you don’t yet know which test your implementation is failing on.

6 videos (Total 48 min), 5 readings, 3 quizzes
6 videos
Solving the Sum of Two Digits Programming Challenge (screencast)6m
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13m
Stress Test - Implementation8m
Stress Test - Find the Test and Debug7m
Stress Test - More Testing, Submit and Pass!8m
5 readings
Companion MOOCBook10m
What background knowledge is necessary?10m
Optional Videos and Screencasts10m
Maximum Pairwise Product Programming Challenge10m
1 practice exercise
Solving Programming Challenges20m
5 hours to complete

Algorithmic Warm-up

In this module you will learn that programs based on efficient algorithms can solve the same problem billions of times faster than programs based on naïve algorithms. You will learn how to estimate the running time and memory of an algorithm without even implementing it. Armed with this knowledge, you will be able to compare various algorithms, select the most efficient ones, and finally implement them as our programming challenges!

12 videos (Total 77 min), 3 readings, 4 quizzes
12 videos
Coming Up3m
Problem Overview3m
Naive Algorithm5m
Efficient Algorithm3m
Problem Overview and Naive Algorithm4m
Efficient Algorithm5m
Computing Runtimes10m
Asymptotic Notation6m
Big-O Notation6m
Using Big-O10m
Course Overview10m
3 readings
3 practice exercises
Growth rate10m
4 hours to complete

Greedy Algorithms

In this module you will learn about seemingly naïve yet powerful class of algorithms called greedy algorithms. After you will learn the key idea behind the greedy algorithms, you may feel that they represent the algorithmic Swiss army knife that can be applied to solve nearly all programming challenges in this course. But be warned: with a few exceptions that we will cover, this intuitive idea rarely works in practice! For this reason, it is important to prove that a greedy algorithm always produces an optimal solution before using this algorithm. In the end of this module, we will test your intuition and taste for greedy algorithms by offering several programming challenges.

10 videos (Total 56 min), 1 reading, 3 quizzes
10 videos
Car Fueling7m
Car Fueling - Implementation and Analysis9m
Main Ingredients of Greedy Algorithms2m
Celebration Party Problem6m
Efficient Algorithm for Grouping Children5m
Analysis and Implementation of the Efficient Algorithm5m
Long Hike6m
Fractional Knapsack - Implementation, Analysis and Optimization6m
Review of Greedy Algorithms2m
1 reading
2 practice exercises
Greedy Algorithms10m
Fractional Knapsack10m
7 hours to complete


In this module you will learn about a powerful algorithmic technique called Divide and Conquer. Based on this technique, you will see how to search huge databases millions of times faster than using naïve linear search. You will even learn that the standard way to multiply numbers (that you learned in the grade school) is far from the being the fastest! We will then apply the divide-and-conquer technique to design two efficient algorithms (merge sort and quick sort) for sorting huge lists, a problem that finds many applications in practice. Finally, we will show that these two algorithms are optimal, that is, no algorithm can sort faster!

20 videos (Total 157 min), 5 readings, 6 quizzes
20 videos
Linear Search7m
Binary Search7m
Binary Search Runtime8m
Problem Overview and Naïve Solution6m
Naïve Divide and Conquer Algorithm7m
Faster Divide and Conquer Algorithm6m
What is the Master Theorem?4m
Proof of the Master Theorem9m
Problem Overview2m
Selection Sort8m
Merge Sort10m
Lower Bound for Comparison Based Sorting12m
Non-Comparison Based Sorting Algorithms7m
Random Pivot13m
Running Time Analysis (optional)15m
Equal Elements6m
Final Remarks8m
5 readings
5 practice exercises
Linear Search and Binary Search10m
Polynomial Multiplication15m
Master Theorem10m
Quick Sort15m
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Top reviews from Algorithmic Toolbox

By SGJan 20th 2017

I liked the fact that the algorithms are not just the introductory searching and sorting algorithms. The assignments are fairly difficult (I have decent scripting experience), but not impossibly so.

By MMSep 29th 2017

good course, I like the fact you can use a lot of languages for you programming exercises, the content is really helpful, I would like to have more indications from the grading system to save time.



Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering

Michael Levin

Computer Science

Neil Rhodes

Adjunct Faculty
Computer Science and Engineering

Pavel Pevzner

Department of Computer Science and Engineering

Daniel M Kane

Assistant Professor
Department of Computer Science and Engineering / Department of Mathematics

About University of California San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

About National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more. Learn more on www.hse.ru...

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....
Data Structures and Algorithms

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.