Data Structures is one of the foundation courses in Computer Science. Essentially, it includes concepts such as stacks, queues, graphs, algorithm analysis, sorting algorithms, linked lists, and set implementations (binary search trees and hash tables). While it is true that data structures and algorithms are difficult to master, it is not an impossible feat. The key to learning these tricky concepts is to follow the right approach, and that’s what we’re going to show you in this post.

**Strengthen Your Fundamentals**

The foremost requirement for mastering data structures and algorithms is a solid foundation of the fundamental concepts of Mathematics, Computer Architecture, and of course Data Structures.

**Maths**– A concrete mathematical base is essential to learn algorithms. Try to cover Math concepts from different areas such as set theory, regular expressions, linear equations, finite-state machines, matrix multiplication, and basic combinatorial principles like pigeonhole, permutations, and combinations.

**Primary Data Structures**– Strengthen your knowledge about the primary data structure concepts like arrays, hash tables, graphs, stacks, queues, heaps, linked lists, and binary trees.

**Computer Architecture**– To be able to work with data structures and algorithms you need to have basic knowledge of computer arithmetic, boolean algebra, floating-point representation, cache design, and digital logic design. If you are well-versed in programming languages such as C, C++, Python, Java, and Ruby, you’ll have the edge over your competitors.

**Learn To Visualize Data Structures**

To become a great coder, one must possess the ability to visualize different data structures. You need to picture how a data structure will look like, how you can implement it within your code, and also how it is organized in your computer ’s memory as well as in the abstract. To visualize data structures, you can pen down your thought pattern on paper. As you gradually master visualization, you’ll find it much easier to solve all kinds of problems, be it simple ones like stacks or be it self-balancing trees.

**Dive Into Algorithms**

Once you’ve learned about the fundamental concepts of data structures, it’s time to leap into algorithms. An excellent way to start would be to learn Big-O notation as it would help you understand how to classify algorithms based on their running time and space requirements. Books like Introduction to Algorithms, and Algorithm Design Manual are great learning options.

As you learn more about algorithms, you should start implementing algorithms in your codes and learn about their running times in real-time. You could try implementing Euclid’s algorithm, Binary search, Binary tree traversals, Dijkstra’s shortest path, Min & max heaps, to name a few. Platforms such as HackerRank, LeetCode, CodeChef, and Coderbyte are excellent for practicing coding and sharpen your coding skills.

**Learn Dynamic Programming**

If you wish to master data structures and algorithms, dynamic programming is a must. It is a technique of solving complicated problems by breaking them down into smaller fragments of “*subproblems*.” These subproblems are then solved at once and their solutions are stored for future reference. Thus, in future if similar problems occur, you don’t need to solve it again from scratch; instead, you can refer to the previous solutions and save both time and effort.

So, there, you have it – your stepwise guide to approaching and mastering data structures and algorithms. If you follow these four steps diligently and with dedicated passion, you can surely master data structures in a matter of few months. And, if you feel stuck anywhere along your journey, don’t forget to check us out at CodingNinjas.in,

Happy learning!