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Best Data Structures and Algorithms Courses 2023

Data Structures and Algorithms Courses. Data structures and algorithms are important to the field of computer science. All other areas of computer science and development are built on top of them. Because of this, companies like Google, Microsoft, and Facebook are searching for programmers with an understanding of data structures and algorithms. Whether you’re trying to advance your career or find a new job, learning DSA may be helpful. You don’t need to spend a lot of money on a college education to learn how to code. Online courses come in handy in these situations. They serve as a fantastic learning tool and competency indicator during interviews.

If you want to learn more about data structures and algorithms, you’ve come to the correct place. For you, we made the effort. To assist you in mastering the skill that employers are seeking the most right now, we looked through the highest rated online courses and hand-picked 15 of the best.

Data Structures and Algorithms Courses

1. Accelerated Computer Science Fundamentals Specialization by University of Illinois

A Coursera Specialization on fundamental computer science algorithms and data structures is available from the University of Illinois. Wade Fagen-Ulmschneider, a professor of computer science, developed a three-course curriculum to give students a path into computing and data science. The program’s coding activities require students to create short pieces of C++ code on a web-based interface. Additionally, there are two projects in each semester that require students to create C++ programs to do tasks like image editing, effective data structure manipulation, or graph search. You’ll discover:

  • Designing and implementing an object-oriented program in C++
  • How to analyze time complexity and space required for an algorithm
  • Selecting and implementing the best data structures that best use the resources to solve a computational problem.
  • To implement and call sophisticated library functions after gaining a solid understanding of object data structures.

The course is adaptable, and students should be able to develop simple programs in any programming language by the end of it. The course lasts for three months.

2. Master the Coding Interview: Data Structures + Algorithms

If you want to work for a top tech company like Google, Microsoft, Facebook, Netflix, Amazon, or another organization but are frightened of the interview process and coding questions, this course is for you. Along with algorithms, this course also covers topics like non-technical interviews and salary negotiations. The subjects covered are:

  1. Technical:
  • Big O notation
  • Data structures:
  1. Arrays
  2. Hash Tables
  3. Singly Linked Lists
  4. Doubly Linked Lists
  5. Queues
  6. Stacks
  7. Trees (BST, AVL Trees, Red-Black Trees, Binary Heaps)
  8. Tries
  9. Graphs
  • Algorithms:
  1. Recursion
  2. Sorting
  3. Searching
  4. Tree Traversal
  5. Breadth-First Search
  6. Depth First Search
  7. Dynamic Programming
  • Non-Technical
  1. How to get more interviews
  2. What to do during interviews
  3. What to do after the interview
  4. How to answer interview questions
  5. How to handle offers
  6. How to negotiate your salary
  7. How to get a raise

The price of the course is 3499 rupees. You need to have a basic understanding of any programming language for this course. The course consists of 261 20-hour lectures.

3. Python Data Structures

The University of Michigan’s Python for Everyone Specialization on Coursera has a course on Python data structures. It provides an overview of the fundamental data structures used in the Python programming language. With a 4.9 rating and approximately half a million students who have previously finished it, this course is among the most well-liked ones. 12 percent of students who successfully completed the course found a real job. subjects covered

This course, which takes 19 hours to complete, offers financial aid. The course’s friendliness for beginners is a plus.

4. Programming Foundations: Algorithms

In this course, author and developer Joe Marini will take you through some of the most well-liked and efficient algorithms for locating and sorting data, using recursion, and comprehending typical data structures. Additionally, he discusses how to assess an algorithm’s performance as well as the effects that different algorithms have on performance. Though Python is used to explain the lessons, they can be used with any programming language. Subjects covered:

  • Common data structures (Arrays, Linked List, Stacks, Queues, Hash Tables)
  • Recursion
  • Sorting
  • Searching
  • Other Algorithms (Unique filtering with hash tables, Finding max value recursively)

A certificate of completion is also provided by LinkedIn, and the course is priced at 1150 Rupees. Anyone with no prior experience can apply for this self-paced course.

5. Advanced-Data Structures-MIT Open courseware

This is a graduate-level course from MIT open courseware. Topics covered include

  • Time travel
  • Geometry
  • Dynamic optimality
  • Memory hierarchy
  • Hashing
  • Integers
  • Dynamic graphs
  • Strings
  • Succinct

6. Data Science Foundations: Data Structures and Algorithms Specialization

This advanced specialization is led by Coursera’s top educator, Sriram Sankaranarayanan. In this course, you will learn to design algorithms and analyze their complexity in terms of running time and space usage, search and sorting algorithms, and how to build applications that support highly efficient algorithms and data structures. You will also learn how to organize, store, and process data efficiently using advanced data structures. The University of Colorado Boulder offers a Master of Science in data science that includes this emphasis. Calculus, probability theory, and some Python programming experience are prerequisites for learners. This course should take three months to complete.

Skills that you’ll gain:

  • Algorithms
  • Dynamic Programming
  • Greedy algorithms
  • Divide and Conquer algorithm
  • Randomized algorithms
  • Sorting algorithms
  • Graphs
  • Data structures
  • Hash Tables
  • Spanning tree
  • NP-completeness

7. Free Algorithms Course by IIT Bombay (edX)

This edX Algorithms course was created by qualified academics from the esteemed Department of Computer Science and Engineering at IIT Bombay. It teaches students how to organize and employ algorithms to address real-world issues as part of IIT Bombay’s Fundamentals of Computer Science XSeries Program. In this computer science course, students learn how to conceive about algorithms and how to build them following the best practices. The following subjects are covered in the course:

  • Sorting algorithms such as quick sort and merge sort
  • Searching algorithms
  • Median finding
  • Order statistics
  • Geometric algorithms like Polynomial Multiplication
  • String algorithms
  • Numerical algorithms
  • Matrix Operations, GCD, Pattern Matching, Subsequences, Sweep, and Convex Hull
  • Graph algorithms like shortest path and spanning tree

8. Algorithms Specialization by Stanford University

This Coursera Algorithms specialization is provided by Stanford University. For significant work in almost every area of computer science, an understanding of the principles of algorithms and related data structures is necessary. In this course, learners are introduced to algorithms, and the emphasis is placed on conceptual knowledge rather than getting straight into low-level implementation and mathematical details. It supports the growth of the participants’ coding and analytical abilities, putting them in a position to pursue serious software engineering, ace technical interviews, and learn more complex algorithmic themes.

Topic covered:

  • Asymptotic (“Big-oh”) notation
  • Sorting and searching algorithms
  • Master method for analyzing algorithms
  • Quicksort algorithm and its analysis
  • Data structures-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

9. Data Structures and Algorithms Specialization Program (Coursera)

This speciality in algorithms and data structures is provided by the National Research Institute Higher School of Economics and the University of California, San Diego. In this curriculum, which offers a strong blend of theory and practice, students study the theory underlying algorithms, implement them in a programming language of their choosing, and utilize them to solve actual problems.

Six courses make up the program, the first two of which address theory and fundamental algorithmic concepts before moving on to more complicated algorithms. It covers the following subjects:

  • Using data structures to solve a variety of problems
  • Graph data structure
  • Graph-based algorithms
  • Algorithms on strings
  • Advanced algorithmic concepts like Network flows, linear programming, and NP-complete problems

10. Introduction to Algorithms

An introduction to computational issues and mathematical modeling is given in this free MIT course. It discusses the most popular data structures, algorithms, and algorithmic frameworks for resolving these problems. The course focuses on how algorithms and programming interact as well as the fundamental performance metrics and analysis techniques for these problems.

What you will learn:

  • Introduction to mathematical modeling of computational problems
  • Common algorithm
  • Algorithm paradigms
  • Data structures
  • Relationship between algorithms and programming
  • Basic performance measures and analysis techniques for these problems.

11. CS50’s Introduction to Computer Science

The Harvard University course CS50x introduces students to the academic fields of computer science and programming, whether or not they have any prior programming expertise. David J. Malan instructs students in CS50x, an introductory computer science course, in which they learn:

  • How to think algorithmically and solve problems quickly
  • Abstraction
  • Algorithms
  • Data structures
  • Encapsulation
  • Resource management
  • Security
  • Software engineering, and
  • Web development

This course includes real-world topics including biology, encryption, economics, forensics, and problem sets with gaming influences. On-campus CS50x is the same as the largest course at Harvard, CS50. Students who complete a final project and nine programming problem sets with an acceptable grade will receive a certificate. You can work through the self-paced course CS50x at your own leisure.

12. Data Structures-by NPTEL

In this NPTEL data structure course, you’ll learn how to design and implement a variety of basic and advanced data structures, introduce different techniques for representing data in the real world, create applications using data structures, teach the concept of data protection and management, and increase the efficiency of any algorithm by using the appropriate data structure.

Topics covered:

  • Introduction to List
  • Array and Linked List
  • Stack Implementation using array and linked list – Applications of Stack
  • Queue Implementation – Application of Queues
  • Trees and Terminologies – Tree Traversals
  • In order Traversal-Binary Search Tree – Implementation of Search Algorithm
  • AVL Tree Insertion, Deletion
  • Graph representation, Shortest Path Algorithm
  • Sorting, Heap Techniques, Hashing
  • Sorting Algorithms, Divide and Conquer algorithms
  • Selection Sort, Brute force sort, Bubble Sort
  • Insertion Sort, Quicksort applications
  • Prim’s Algorithm, Kruskal’s Algorithm
  • Bucket Sorting, Radix Sort, Merge Sort
  • Directories and Contiguous allocation, File maintenance
  • External Sorting, Cascade Merge Sort
  • B + Tree maintenance and efficiency, Construction of B-tree, B+tree insertion and deletion

FAQS on Data Structures and Algorithms Courses

Why are Data structures and algorithms important?

Data structures and algorithms are crucial for developers because they demonstrate their aptitude for solving problems, which is the skill that employers respect the most. Programmers that are proficient in data structures and algorithms can process data, reason, and do computations with ease.

Can I learn algorithms and data structures in Python?

Yes, Python allows you to study data structures and algorithms.

Where are algorithms and data structures used?

Every area of computer science uses DSA (Data Structure and Algorithm). Algorithms are used to use the data that is stored in data structures to solve problems.


Data structures and algorithms can be learned in a wide variety of courses, but few of them strike the ideal mix between theory and application. The courses that we discussed in this post provide a nice balance between these two computing facets.

Additionally, they include every idea you would require to code something applicable to the outside world. Anyway, I believe this information is sufficient for you to decide which course you should enroll in next. Select one of them to begin your journey toward landing a job with the organization of your dreams!

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