How Data Structures and Algorithms are important for Computer Science Graduates?

Many a times Computer Science graduates devalue the importance of learning data structures and algorithms considering it as complicated, irrelevant or a waste of time. However, they soon get a reality check when they enter the real-word for job hunting. Big companies like Amazon, Google or Microsoft often ask questions related to algorithms and data structures to check the problem-solving abilities of the candidates.

Both the concepts are extremely important to learn for CS students if they want to advance their careers and secure high-paying jobs in the programming world. We in this blog are evaluating the importance of learning data structures and algorithms for tech aspirants.

What is a Data Structure?   

To simply put, data structure is an orderly arrangement of data in computers to use it in a more efficient manner. It is a collection of data objects that allows storing, organizing, and retrieving data on systems.

A majority of data structures are inspired from real life scenarios. For instance, have you been scolded by your parents for not being able to find a particular outfit in your messy wardrobe? Yes, right? Your parents give the advice to keep your clothes in a systematic manner so the next time you want something you can easily pick it up. In this situation, you need to arrange & keep your clothes (data) in such a structure that when searching for a particular thing you don’t have to hassle much.

We are using data structures in our everyday lives without even knowing it. From our contact list, book piles to organizing hierarchy or to-do list, we are applying different arrangement techniques which are called as data structures in the computing realm. Data structure provides the right way to organize information in the digital space.

The data structure is a key component of Computer Science and is largely used in the areas of Artificial Intelligence, operating systems, graphics, etc.

Data structures store objects and allow their manipulation on the basis of two different types:

What is an Algorithm?

Algorithm refers to a set of steps used in completing a certain task or to get a desired output. It is like building blocks for programming that allows smartphones, computers or websites to function smoothly and make decisions. Each code written by a programmer is a collective formation of algorithms navigating what to do. Algorithms are well-defined procedures that help computers to solve problems.

Let’s take a simple example of GPS. When you search a location, GPS uses an algorithm to search for multiple available routes, also for checking the current traffic GPS uses a different algorithm, based on the collective information it provides the best available route for you. All these algorithms are in-built   into the GPS’ code. So, if there is any error in the code of GPS, it won’t function correctly, thus provide incorrect direction. Computers use algorithms to calculate things much faster than the humans.

Relationship between Data Structures and Algorithm

Both Data structures and algorithms are interrelated and complement each other. An algorithm applies to a particular data structure, while using the right data structure helps to drastically improve the performance of an algorithm. Hence, we can’t detach data structures and algorithms.

Following are the main categories of algorithms in relation to data structures:

  • Search– This algorithm helps in finding an item in a data structure.
  • Insert– To insert an item in a data structure, this algorithm is applicable.
  • Sort– This algorithm is helps to sort items in a specific order.
  • Update– The update algorithm is useful for updating an existing item in a data structure.
  • Delete– In order to delete an existing item from a data structure, you can use the delete algorithm.

Reason to Learn Data Structures and Algorithms

Data structures and algorithms are the most pivotal topics for programmers and Computer Science graduates, to get a job & perform well in it. Here are some considerable reasons to learn data structures and algorithms:

  • A comprehensive knowledge of data structures in combination with algorithms is the core foundation of writing good codes. It reduces coding costs & enhances data accuracy, which is the ultimate goal of organizations.
  • To earn salaries as high as the developers of Amazon and Google, you need to improve your problem-solving abilities by mastering data structures and algorithms.
  • If you want to generate bug-free results in coding, then it is utmost important to excel these concepts.
  • Learning data structures and algorithms is also beneficial for a better understanding of new frameworks such as Angular, React, Vue, Spring MVC, etc.
  • When you get an exposure to a different range of problem-solving techniques, it helps you take up the next challenging problem easily.
  • Programmers who are competent in data structures and algorithms can easily perform the tasks related to data processing, automated reasoning, or calculations. 
  • Data structure and algorithm is significant for developers as it shows their problem-solving abilities amongst the prospective employers. Thus, amplifies the chances of getting the job.

The choice of data structure & algorithm can make a huge difference between a program running in few seconds to many days. You can only make a great choice if you have that level of premier knowledge about data structures and algorithms.

Data Structures and Algorithms Topics to Learn for Competitive Programming

Data structure and algorithm is a vast subject altogether, however there are some key topics you must prepare before going for an interview:

  • Role of Algorithms and Data Structures in problem solving
  • Types of Data Structures
  • Identifying techniques for designing Algorithms
  • Sorting Data by using Bubble Sort Algorithm
  • Performing Linear Search
  • Sorting Data by using Selection Sort Algorithm
  • Implementing Binary Search
  • Sorting Data by implementing Shell Sort Algorithm
  • Dynamic Memory Allocation
  • Inserting a Node in a Linked List
  • Traversing a Doubly-Linked List
  • Implementing a Circular Linked List
  • Sorting Data by implementing Merge Sort Algorithm
  • Adding Polynomials Using Linked Lists
  • Implementing a Stack using an Array
  • Implementing a Stack using a Linked List
  • Identifying various operations on Queues
  • Implementing a Queue using an Array
  • Hashing              
  • Storing Data in a Tree
  • Implementing a Binary Search Tree
  • Indexing & defining a Threaded Binary Tree
  •  Height Balanced Tree  
  • Graph Storing Data in a Graph
Data Structure and Algorithm Tree

Tip– Use LeetCode and Hacker Rank to practice your coding skills as the more you practice, the more you will become competent for a good job.

Conclusion

The technology will only be going to become better at what it does as long as programming & coding continues to flourish. Therefore, the importance of data structures and algorithms will remain persistence for the functioning of technologies, navigating what they do & how they do it.

Ideally all Computer Science students must learn data structures and algorithms during the course of their graduation, but universities usually overlook these topics. So, the only source of learning these concepts is by enrolling in a technology upskill program. If you want to improve your algorithms and data structures knowledge, you are on the right platform. We teach all the major topics of Data Structures and Algorithms.

Let’s help you achieve your career goals. SynergisticIT- The Best Programmers in the Bay area…Period!

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