10 Best Data Structure and Algorithms Courses for Coding Interviews

These are the best online courses to learn Data Structures and Algorithms from Udemy, edX, Programmerspace, Learnbay and Coursera for coding interviews.

Hello guys, if you are preparing for Coding interviews and looking for the best Data Structure Algorithms courses then you have come to the right place. Data Structures Algorithms is one of the most difficult topics and many candidates fail to answer questions related to Data Structure, each code line may require some hundreds of programming instructions to execute, in a dual stack, recursive descent parsing algorithm.

I have been sharing useful courses for coding interviews for quite some time like earlier, I have shared best algorithms courses, Adobe Illustrator courses, Python, Data Structure, and System Design courses for programmers, and today, I am going to talk about the best online courses to master Data Structure for interviews.

These Data Structure courses have been chosen from popular online learning platforms and websites like Udemy, Coursera, edX, and Educative, Learnbay and these are created by experts who have seen the interviews from both sides of the table.

Along the way, I have also shared useful techniques where you can learn about some popular Data Structures questions like Geeksforgeeks and designing a UI using data science and data analytics.

Our team of global experts have compiled this list of the 10 Best Data Structures Certification, Tutorial, Course, Classes & Training program available online in 2021 to help you learn Data Structures. These are suitable for beginners, intermediate learners as well as experts. Also, if you are interested, do check out Best Data Structure Algorithm Certification.

10 Best Data Structure Algorithm Courses for Programmers and Developers

Without wasting any more of your time, here is my list of some of the great, interactive, and fun online courses to learn Data Structure Algorithms. These are truly the best online courses you can join to learn this essential skill or improve your Data Structure skill.

1. Data Structures and Algorithms Specialization Program (Coursera)

This specialization in algorithms and data structures is offered by University of California, San Diego and National Research Institute Higher School of Economics. The program is a good mix of theory and practice where students learn the theory behind algorithms, implement them in a programming language of their choice and apply them to solve practical problems. The program comprises of 6 courses, starting with theory and basic algorithmic techniques, and then gradually moves to advanced algorithms and complexity. It covers following topics:

• Using data structures in various computational problems.
• Graph data structure.
• Algorithms on graphs.
• Algorithms on strings.
• Advanced algorithmic concepts like Network flows, linear programming and NP-complete problems.

The philosophy of this data structures and algorithms course is learning through doing. Every module comprises of 1–2 hours of video lectures, with some embedded quizzes, followed by code solutions to the problem set. Major highlight of this program is specially created 100 algorithmic coding challenges that help to turn a learner into a pro in algorithmic design. The solutions to these challenges are checked automatically against 15+ test cases. These help students learn how to implement, test and debug fast algorithms for solving large and difficult problems in seconds. Another important feature is that this program is language-agnostic. Every lecture has pseudocode, and requires students to translate what’s conceptually laid out into code. This greatly enhances their skill and learning. The specialization includes two real world projects — Big Networks (which involves finding Shortest Paths in Road Networks and Social Networks using algorithms which are thousands of times faster than the classic ones) and Genome Assembly (which involves bioinformatics algorithms to assemble a genome from millions of short DNA fragments).

We can learn through this course:

• Apply basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.
• Apply various data structures such as stack, queue, hash table, priority queue, binary search tree, graph and string to solve programming challenges.
• Apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.
• Solve complex programming challenges using advanced techniques: maximum flow, linear programming, approximate algorithms, SAT-solvers, streaming.

Duration : 6–8 months, 6 hours per week; Rating : 4.6

2. Algorithms Specialization by Stanford University (Coursera)

This Coursera Algorithms specialization is a MOOC offered by Standford University. Understanding the basics of algorithms and related data structures is essential for doing serious work in almost any branch of Computer Science. Therefore Stanford has mandated a version of this course in curriculum of their every Computer Science degree program — bachelors, masters as well as PhD. This specialization introduces learners to algorithms and focuses on conceptual understanding instead of delving into mathematical details and low-level implementation straight away. It helps to develop the programming and thinking skills of the participants so that they are well positioned to pursue serious software engineering, ace technical interviews and study more advanced topics in algorithms. There are 4 courses in this program that cover following topics:

• Asymptotic (“Big-oh”) notation, sorting and searching algorithms.
• Master method for analyzing divide and conquer algorithms.
• Quick Sort algorithm and its analysis
• Data structures like heaps, balanced search trees, hash tables, bloom filters.
• Dijkstra’s shortest-path algorithm.
• Breadth-first and depth-first search and its applications.
• Greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes).
• Dynamic programming (knapsack, sequence alignment, optimal search trees)
• Shortest paths algorithms (Bellman-Ford, Floyd-Warshall, Johnson)
• NP-complete problems and exact and approximation algorithms for them.
• Local search algorithms for NP-complete problems.
• Strategies for coping with computationally intractable problems like analysis of heuristics.

Several types of assessments are included throughout these courses, from multiple choice quizzes at the end of each module and each course to weekly programming assignments where students are required to implement the algorithms taught in the lesson in a programming language of their choice. It is assumed that students know how to program in at least one programming language (like C, Java or Python).

Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.

Duration : 16 weeks, 3 hours per week; Rating : 4.8

3. Free Algorithms Course by Princeton University (Coursera)

This is a two-part course series on algorithms offered for free by Princeton University. Both the courses have been very well received by the students making them one of the highest ranked algorithms courses on Coursera with a rating of 4.9 out of 5. The courses provide an introduction to algorithms and data structures with emphasis on applications and scientific performance analysis of Java implementations. Though the concepts are language independent, the solutions and implementations are done in Java.

1. Algorithms, Part I — It covers elementary data structures (like linked lists, stacks, queues, binary heaps, and hash tables etc.) and sorting & searching algorithms (like binary search, quicksort, mergesort, insertion sort, selection sort, shellsort etc.)
2. Algorithms, Part II — It focuses on graph and string processing algorithms and more advanced concepts used in application development. It covers undirected graphs, directed graphs, minimum spanning tree problem, shortest-paths problems, maximum flow and minimum cut problems and algorithms used for solving these problems.

The instructors of these courses Kevin Wayne and Robert Sedgewick are highly acclaimed and expert authors and lecturers. Robert Sedgewick has also authored Algorithms book along with Kevin Wayne, which is one of the best books to learn Data Structure and Algorithms in Java. This course series focuses on understanding algorithms by implementing and testing them. It assumes that students have basic familiarity with Java and requires that all programming assignments be submitted in Java. All the course materials are available for free including the graded assignments and no certificate is offered upon completion of the courses.

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. All the features of this course are available for free. It does not offer a certificate upon completion. Whereas, Princeton University is a private research university located in Princeton, New Jersey, United States. It is one of the eight universities of the Ivy League, and one of the nine Colonial Colleges founded before the American Revolution.

Duration : 6 weeks, 8–10 hours per week; Rating : 4.9

4. Data Structure and Algorithm using Java (Learnbay)

In this course, you will learn data structures and algorithms by solving 300+ practice problems. The prerequisites are: java, C,C# programming languages. You will begin each course by learning to solve defined problems related to a particular data structure and algorithm. By the end of each course, you would be able to evaluate and assess different data structures and algorithms for any open-ended problem and implement a solution based on your design choices.

Duration : 2.5 months to complete; At 6 hrs/week.

5. Data Structure and Algorithm using Python (Learnbay)

In this course, you will learn data structures and algorithms using Python by solving 300+ practice problems. You will begin each course by learning to solve defined problems related to a particular data structure and algorithm. By the end of each course, you would be able to evaluate and assess different data structures and algorithms for any open-ended problem and implement a solution based on your design choices.

Duration : 2.5 months to complete;

6. Data Structures and Algorithms Nanodegree Certification (Udacity)

Udacity offers a Nanodegree program in Data Structures and Algorithms. In this program students learn data structures and algorithms and how to use them to solve a wide range of real world problems. It is a very hands-on program, heavy on algorithms and includes 100+ practice problems. There are following 4 courses in this nanodegree program:

1. Welcome — This is a program overview and a Python refresher. Here students deconstruct a series of open-ended problems into smaller components (eg. inputs, outputs, series of functions).
2. Data Structures — It covers different data structures, and methods used to manipulate these data structures. It explores the advantages and applications of different data structures. Here students solve a series of open-ended practice problems such as LRU Cache, Private Blockchain, File Recursion, and many more.
3. Basic Algorithms — It covers basic algorithms such as searching and sorting on different data structures and how to implement these algorithms using both recursion and without recursion. Here students work on a series of real-world open-ended problems, such as request routing for a web server, search-term auto-completion and Fibonacci heap.
4. Advanced Algorithms — It covers advanced algorithms such as brute-force greedy algorithms, graph algorithms and dynamic programming which optimizes recursion by storing results to sub problems. Here students implement a route planner algorithm to calculate the shortest path between two points on a map (like the one used in Google Maps).

In this program, you’ll be using Python to implement the algorithms and therefore Udacity expects that you have an intermediate level knowledge of Python programming language and basic knowledge of algebra.

We will begin each course by learning to solve defined problems related to a particular data structure and algorithm. By the end of each course, you would be able to evaluate and assess different data structures and algorithms for any open-ended problem and implement a solution based on your design choices. Learn and implement basic algorithms such as searching and sorting on different data structures and examine the efficiency of these algorithms. Use recursion to implement these algorithms and then learn how some of these algorithms can be implemented without recursion. Practice selecting and modifying these algorithms for a variety of interview problems.

Duration : 4 months, 10 hours per week; Rating : 4.6

7. MicroMasters Program in Algorithms and Data Structures by UC San Diego (edX)

This eight-course Algorithms and Data Structures program is offered on edX by University of California, San Diego. It aims to help students master the algorithmic programming techniques and get a job. The focus of this program is on learning through application, so course creators have invested thousands of hours in designing over one hundred algorithm challenges. Learners solve various computational problems through implementing these algorithmic coding challenges in a programming language of their choice. The 8 courses in this program cover the following topics:

1. Algorithmic Design and Techniques — Learn how to design algorithms, solve computational problems and implement solutions efficiently.
2. Data Structures Fundamentals — Learn about data structures that are used in computational thinking — both basic and advanced.
3. Graph Algorithms — Learn how to use algorithms to explore graphs, compute shortest distance, min spanning tree, and connected components.
4. NP-Complete Problems — Learn about NP-complete problems, known as hard problems that can’t be solved efficiently, and practice solving them using algorithmic techniques.
5. String Processing and Pattern Matching Algorithms — Learn about pattern matching and string processing algorithms and how they apply to interesting applications.
6. Dynamic Programming — Learn how dynamic programming and Hidden Markov Models can be used in machine learning and genomics to compare genetic strings and uncover evolution.
7. Graph Algorithms in Genome Sequencing — Learn how graphs are used to assemble millions of pieces of DNA into a contiguous genome and use these genomes to construct a Tree of Life.
8. Algorithms and Data Structures Capstone Project — Synthesize your knowledge of algorithms and biology to build your own software for solving a biological challenge.

The MicroMasters program offers learners a credential for career advancement at Rochester Institute of Technology (RIT) upon successful completion of the seven courses and the Capstone Project. If a learner applies for admission to the RIT’s Master of Science in Professional Studies program at as part of the university’s School of Individualized Study (SOIS), and is accepted, the edX MicroMasters program certificate will count towards 25% of the coursework required the M.S. degree at RIT.

This program is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems through implementing over one hundred 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 have invested thousands of hours designing challenges as an alternative to multiple choice questions that you usually find in MOOCs. We believe in learning through application, especially when it comes to learning algorithms.

Duration : 9 months, 8–10 hours per week; Rating : 4.7

8. JavaScript Algorithms and Data Structures Masterclass (Udemy)

This class on algorithms and data structures in Javascript by Colt Steele is amongst the most highly rated and reviewed courses on this subject on Udemy. Whether one is looking to ace a coding interview or become a better programmer or improve one’s problem solving skills, this course turns out to be a great fit as it focuses on building a complete computer science foundation so that one can solve any computational problem. The course packs months of computer science and interview prep material into about 22 hours of video lessons. Colt has drawn the content of this course directly from his in-person coding bootcamps that have helped several of his students to crack interviews at huge companies like Google, Tesla, Amazon and Facebook. The course starts with the basics and then gradually covers advanced topics like Heaps, Graphs etc. It teaches the following topics:

• How to assess your own code and compare algorithms as far as time and space complexity is concerned using Big O notation Details of Recursion.
• Five step approach to solving any coding problem.
• Programming patterns and interview strategies.
• Dozens of algorithms including searching and sorting algorithms.
• More than 10 data structures and how to implement them from scratch.
• How to traverse trees and graphs.
• Dijkstra’s Shortest Path Algorithm.
• Dynamic Programming.

This is a very interactive course with over 85 coding exercises where students are expected to try out every problem on their own before the instructor walks them through solution options. Apart from video lectures, it includes 32 articles and 80 downloadable resources.

We start by teaching you how to analyze your code’s time and space complexity using Big O notation. We cover the ins and outs of Recursion. We learn a 5-step approach to solving any difficult coding problem. We cover common programming patterns. We implement popular searching algorithms. We write 6 different sorting algorithms: Bubble, Selection, Insertion, Quick, Merge, and Radix Sort. Then, we switch gears and implement our own data structures from scratch, including linked lists, trees, heaps, hash tables, and graphs. We learn to traverse trees and graphs, and cover Dijkstra’s Shortest Path Algorithm.

Duration : 21.5 hours on-demand video; Rating : 4.7

9. Python for Data Structures, Algorithms, and Interviews (Udemy)

This Udemy data structures and algorithms course is offered by Jose Portilla, who has taught thousands of students about Python programming and Data Science. He has created this course to help students with the coding interview process at the top technology companies. It is basically a three-in-one course that covers data structures and algorithms in Python and technical coding interview questions along with solutions to them and non technical interview preparation like resume reviews and in-person interview prep. The course content is spread over 200+ video lectures that explain a particular topic, accompanied by a notebook of written code and explanations. Primarily the course focuses on the following:

• Non-technical interview preparation — covers creating resume, creating LinkedIn and Github profiles, post-interview topics related to salary negotiation and references preparation).
• Data Structures and Algorithms — covers algorithm analysis and Big-O notation, array sequences, stacks queues and deques, linked lists, recursion, trees, searching and sorting algorithms, graph algorithms etc.
• Practice interview coding problems
• Tech company mock interviews.

This course is a great fit for students and professionals who know Python and want to learn about data structures and algorithms and also prepare for tech interviews.

This is the most comprehensive course online to help you ace your coding interviews and learn about Data Structures and Algorithms! This course takes advantage of the easy to read Python programming language to efficiently teach you what you need to know to land the tech job of your dreams! We will learn:

• Create a great resume.
• Have a LinkedIn and Github profile for recruiters.
• Understand all major Data Structures and Algorithms.
• Ace coding interviews after preparing with the course’s mock interviews.

Duration : 16.5 hours on-demand video; Rating : 4.4

10. Data Structures and Algorithms: Deep Dive Using Java (Udemy)

This course by Tim Buchalka and his team is one of the best data structures and algorithms course in Java on Udemy. It focuses on the implementations of data structures and algorithms to give learners a complete understanding of how things work, rather than just theory alone. What makes this course unique is that spends a lot more time looking at what’s available in the JDK, so students better understand how things work under the hood and can apply this understanding to their own future programming projects. The course covers the following topics:

• Big O notation
• Arrays
• Linked Lists
• Binary trees, balanced trees like AVL trees and Red-black trees
• Stacks
• Queues
• Hashtables
• Heaps including heapsort algorithm
• Associative arrays.
• Dictionaries.
• Graph algorithms.
• Sort algorithms.
• Search algorithms.

This course is ideal for those who have some Java programming skills and are looking to obtain a good understanding of data structures and algorithms. But even experienced developers will find this course useful. Those looking to find their first or next better programming job or freelance as a software developer will also benefit immensely from this course.

We will learn:

• The strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications.
• Code an implementation of each data structure, so you understand how they work under the covers.
• Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets.
• Learn what’s available in the JDK for storing and sorting data, so you won’t waste time reinventing the wheel

Duration : 16 hours on-demand video; Rating : 4.4