Top 10 Free Data Structure Courses
Tags: beginners
Published: 2020-06-12 15:21:41

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In this blog, I will be mentioning some of the resources for Data Structure that have **_quality content plus free_**.

Algorithm and Data Structure are two of the most important things required if you want to clear an interview for big and high paying product-based companies.

Also, someone who has good knowledge of the above two will take better decision while implementing a solution and write code which can handle incremental changes in a better way.

Some of the popular concepts of DS and Algos array, linked list, circular linked list, double linked list, binary search tree, graph, heap, stack, queue, etc.

#### 1. [Data Structures and Algorithms Specialization](https://www.coursera.org/specializations/data-structures-algorithms) (Basic to Intermediate)

This course is from Coursera. This is a specialization type of course so instead of one course, this is divided into four separate courses. Although for getting the certification you need to pay, if you are looking for knowledge you can attend this course for free.

This course is offered by UNIVERSITY OF CALIFORNIA SAN DIEGO.

The four different parts of the course:

-   [**Algorithmic Toolbox**](https://www.coursera.org/learn/algorithmic-toolbox?specialization=data-structures-algorithms)**:** The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming.
-   [**Data Structures**](https://www.coursera.org/learn/data-structures?specialization=data-structures-algorithms)**:** In this course, they will consider the common data structures that are used in various computational problems. Also, you will learn how these data structures are implemented in different programming languages.
-   [**Algorithms on Graphs**](https://www.coursera.org/learn/algorithms-on-graphs?specialization=data-structures-algorithms)**:** In this course, you will first learn what a graph is and what are some of the most important properties. Then you’ll learn several ways to traverse graphs and how you can do useful things while traversing the graph in some order.
-   [**Algorithms on Strings**](https://www.coursera.org/learn/algorithms-on-strings?specialization=data-structures-algorithms)**:** We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. In this course, you will learn the string algorithm which search engines use.

#### 2. [Algorithms Specialization](https://www.coursera.org/specializations/algorithms) (Advanced)

This course is from Coursera. This is a specialization type of course so instead of one course, this is divided into four separate courses. Although for getting the certification you need to pay, if you are looking for knowledge you can attend this course for free.

This course is very much at the advanced level then compare to the above specialization. So I would say first go for [Data Structures and Algorithms Specialization](https://www.coursera.org/specializations/data-structures-algorithms) then select this one.

This course is offered by Stanford.

The four different parts of the course:

-   [**Divide and Conquer, Sorting and Searching, and Randomized Algorithms**](https://www.coursera.org/learn/algorithms-divide-conquer): The primary topics in this part of the specialization are: asymptotic (“Big-oh”) notation, sorting and searching, divide and conquer (master method, integer, and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
-   [**Graph Search, Shortest Paths, and Data Structures**](https://www.coursera.org/learn/algorithms-graphs-data-structures): The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
-   [**Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming**](https://www.coursera.org/learn/algorithms-greedy)**:** The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
-   [**Shortest Paths Revisited, NP-Complete Problems**](https://www.coursera.org/learn/algorithms-npcomplete)**:** The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).

#### 3. [**Algorithms 1**](https://www.coursera.org/learn/algorithms-part1) **(Basic)**

This course is from Coursera. This is not a specialization, it’s a separate course. This course is free for everyone also there will be no certification given to anyone.

This course is offered by Princeton University.

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. Part I _covers elementary data structures, sorting, and searching algorithms_.

#### 4. [Algorithms 2](https://www.coursera.org/learn/algorithms-part2) (Intermediate)

This course is from Coursera. This is not a specialization, it’s a separate course. This course is free for everyone also there will be no certification given to anyone.

This course is offered by Princeton University.

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. Part II _focuses on graph- and string-processing algorithms_.

#### 5. [Intro to Data Structures and Algorithms](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513) (Basic)

This course is from Udacity. This course will cover the following topics _data structures and algorithms Searching & Sorting, Maps & Hashing, Graph, Trees_. Also, this course will cover some case studies, introduce you to technical interviewing techniques, and practice interviews.

It’s good for the people who are new to DS and know a little bit of Python, as the coding will be in Python programming language.

#### 6. [Algorithms and Data Structures](https://www.edx.org/course/algorithms-and-data-structures) (Basic)

It’s a free course from eds. Although for getting the certification you need to pay, if you are looking for knowledge you can attend this course for free.

This course is offered by Microsoft.

This course will cover the following topics _Algorithmic Analysis, Sorting and Searching of Algorithms, Data Structures, Linked lists, Stacks, Queues_. As it starts from basic it’s good for people with zero or no knowledge of data structures and algorithms.

#### 7. [**Must Do Interview Preparation**](https://practice.geeksforgeeks.org/courses/must-do-interview-prep?vb=144) **(Basic to Intermediate)**

This is a free course offered by geeksforgeeks. This course is based on the most frequently asked questions in product-based companies. It will help to boost your preparation for different interview rounds in tech giants. The course will have programming questions from intermediate to advanced level.

The concepts covered in this course are _arrays, String, LinkedList, Stack, Queue with some advance interview-based questions_.

#### 8. [Algorithms](https://www.youtube.com/watch?v=0IAPZzGSbME&list=PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O) (Basic-Intermediate-Advance)

Though it’s a youtube course, it covers the algorithms from basic to advanced concepts, and obviously its free of cost.

The concepts covered in this course include _divide & conquer, recursion, binary search, heap sort, merge sort, quick sort, Huffman coding, Dijkstra algorithm, 0/1 knapsack, graph, tree, stack, queue, and linked list_.

#### 9. [Introduction to Algorithms and Data structures in C++](https://www.udemy.com/course/introduction-to-algorithms-and-data-structures-in-c/) (Basic)

It’s a free course from Udemy. It gives concept related to very basic data structures like _Fibonacci sequence, Dynamic programming, 0/1 Knapsack problem, Stack, check parenthesis expression questions, Queue_.

It’s good for the people who are new to DS and know a little bit of C++, as the coding will be in C++ programming language.

#### 10. [Data Structure — Part I](https://www.udemy.com/course/data-structures-part-1-lognacademy/) (Basic)

It’s a free course from Udemy. The topics covered in the course are among the most fundamental material in all of computer science. The students will not only understand the working behavior of data structures but also be able to implement those from scratch. The course will cover well-known data structures such as _dynamic arrays, linked lists, stacks, queues, and trees_.

It’s good for the people who are new to DS and know a little bit of Java, as the coding will be in Java programming language.

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I hope this blog will help you to get a goods resource for learning Data Structures & Algorithms. I would say start with the basic start type course then go to intermediate and advance one. In this way your learning curve will be much better.

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