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Both 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 in the USA for tech aspirants.
What is a Data Structure?
Simply put, the data structure is an orderly arrangement of data in computers to use it more efficiently. It is a collection of data objects that allows storing, organizing, and retrieving data on systems.
Real-life scenarios inspire a majority of data structures. 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 advise you 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 you don’t have to hassle much when searching for a particular thing.
We use data structure in our everyday lives without even knowing it. From our contact list and book piles to organizing hierarchy or to-do list, we apply different arrangement techniques called a data structure in computing. 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.
Types of Data Structures
A data structure stores object and allows their manipulation based on two different types:
Linear Data Structure:
In the linear data structure, the elements are arranged one after the other in a particular sequence. This type of data structure is not suitable for complex programs. Some popular linear data structures are arrays, queues, linked lists, and stacks.
Non-Linear Data Structure:
As the name suggests, the non-linear data structure does not arrange elements in a particular sequence; rather, they’re arranged in a hierarchical order, wherein one element is connected to another or more elements. For example, sets, trees, graphs, and tables.
You can learn to apply linear and non-linear data structures in a Technology Bootcamp in California.
What is an Algorithm?
An algorithm refers to a set of steps used to complete 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 a programmer writes is a collective form of algorithms navigating what to do. Algorithms are well-defined procedures that help computers solve problems.
Let’s take a simple example of GPS. When you search for 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 an error in the GPS code, it won’t function correctly, thus providing incorrect direction. Computers use algorithms to calculate things much faster than humans.
Relationship between Data Structures and Algorithm
Both are interrelated and complement each other. An algorithm applies to a particular data structure while using the right data structure helps drastically improve an algorithm’s performance. Hence, we can’t detach data structures and algorithms.
The 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 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
Both 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 in the USA:
- 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 important to excel in data structures and algorithms.
- Learning data structures and algorithms is also beneficial for a better understanding new frameworks such as Angular, React, Vue, Spring MVC, etc.
- When you get exposure to a different range of problem-solving techniques, it helps you take up the next challenging problem easily.
- Programmers competent in data structures and algorithms can efficiently perform tasks related to data processing, automated reasoning, or calculations.
- It is significant for developers as it shows their problem-solving abilities amongst prospective employers. Thus, amplifying the chances of getting the job.
The choice of data structure & algorithm can make a huge difference between a program running in a 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. So, consider joining a trusted Software Bootcamp in bay area to gain a deep understanding.
Data Structures and Algorithms Topics to Learn for Competitive Programming
It’s a vast subject altogether. However, there are some key topics you must prepare before going for a technical 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
Tip– Use LeetCode and Hacker Rank to practice your coding skills; the more you practice, the more you will become competent for a lucrative job.
Conclusion
The technology will only become better at what it does as long as programming & coding continues to flourish. Therefore, the importance of data structures and algorithms will remain persistent for the functioning of technologies, navigating what they do & how they do it.
Ideally, all Computer Science students must learn data structures and algorithms in the USA 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 Data Science Bootcamp. 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.
Anytime you want to upgrade your skills and need a helping hand to enter or reenter the tech workforce with high-demand tech skills, reach out to us. Since 2010 we have helped 1000’s of jobseekers achieve success in the technology sector. SynergisticIT’s career-oriented training programs guarantee fast-paced, quality tech education, preparing you with top-notch skills for coveted tech roles in the industry. Reach out to us. SynergisticIT– Home of the Best Data Scientists and Software Programmers in the Bay Area!