Datastructures & Algorithms is a very important and foundational topic in Computer Science & Information Technology for Software Developers. It forms the basis of all software development tasks. However, learners often get lost in the vast world of Data structures & Algorithms. We, at Meritstore, have thus decided to streamline the whole Data structures and algorithms syllabus so that you can study the topic with ease.
What are Data structures?
Data structures are fundamental components of computer science that organize and store data in a computer’s memory. They provide efficient ways to manage, access, and manipulate data, enabling algorithms to operate more effectively.
Types of Data Structures
There are two types of data structures – Linear & non-linear. Linear data structures are data structures in which elements are stored in a sequence. E.g. Arrays where each element is in a sequence. Non-linear data structures are those data structures in which elements are not stored in a sequence. E.g. Trees, where elements are not in a sequence in memory but at different positions based on tree structure.
List of Linear Data structures:
List of Non-linear Data Structures:
Data structure Operations
The next important point is being able to operate different functions/operations on each of the above-mentioned data structures. You need to learn operations like Traversal, Insertion, Modification, Deletion, Search, and Sort on each data structure.
Time and Space Complexity Analysis
Time & Space complexity refers to the amount of time & memory space consumed with respect to the amount of inputs provided.
Types of Algorithms
(These are algorithms which are not specific to any particular data structure and can be applied to any data structure):
- Recursion
- Dynamic Programming
- Backtracking
- Greedy Algorithm
So, we hope we have streamlined the syllabus and now you have a clearer view of how to ace Data structures and Algorithms. The blog post contains many links to learn further each topic in detail.
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