Bad programmers worry about the code. Good programmers worry about data structures and their relationships – Linus Torvalds
Let’s help you become a good programmer!
Data Structures are the foundations of software development, and Algorithms are efficient methods for solving specific programming problems. A data structure is a type of storage that is used to store and organize data. It is a method of organizing data on a computer so that it can be easily accessed and updated.
A data structure is used for more than just organizing data. It is also used for data processing, retrieval, and storage. Data structures of various basic and advanced types are used in almost every program or software system that has been developed. As a result, we must be well-versed in data structures.
Learning Data Structures and Algorithms has always been one of the most important concepts for a software developer to understand. The web developer course helps beginners to efficiently learn DSA by providing opportunities to interact with experienced professionals in the industry.
It is unavoidable to learn and solidify your foundations in Data Structures and Algorithms in order to crack coding interviews with imminent product-based companies such as the MAANG companies. Practice DSA interview questions to get a job in such companies.
The best part about learning Data Structures and Algorithms is that this knowledge will never be out of date, and the concepts you learn will help you grow as a developer in the long run.
Data Structure Classification:
- Linear data structure: A linear data structure is a data structure in which data elements are arranged sequentially or linearly, with each element attached to its previous and next adjacent elements. Arrays, stacks, queues, linked lists, and other linear data structures are examples.
- Static data structure: A static data structure has a set amount of memory. A static data structure makes it easier to access the elements. An array is an example of this data structure.
- Dynamic data structure: The size of a dynamic data structure is not fixed. It can be randomly updated during runtime, which may be considered efficient in terms of the code’s memory (space) complexity. Queues, stacks, and other data structures are examples of this type.
- Non-linear data structure: Non-linear data structures are data structures in which data elements are not placed sequentially or linearly. We cannot traverse all of the elements in a non-linear data structure in a single run. Trees and graphs are examples of non-linear data structures. Using the array data structure, for example, we can store a list of items with the same data type.
Now, the most effective way to learn Data Structures and Algorithms is dependent on several factors:
- Prior knowledge of programming languages, as well as basic DS and Algos.
- The reason why you want to learn it.
- The resources at your disposal.
- A fantastic guide.
Let us now look more closely at each of the points raised above:
- Prior knowledge of DS and Algo: If you are already familiar with basic data structures such as Arrays, Linked Lists, and some basic algorithms such as Sorting, Searching, and so on, you will take much less time than a complete newbie.
- The goal of learning DS and Algo: It also depends on why you want to improve your knowledge of Data Structures. Some learn them for job interviews, others for competitive programming, and still others for general knowledge. If you are preparing for a job interview, you will have a limited set of Data Structures to learn that are most commonly asked in interviews; however, if you want to become a good competitive programmer, you will have to focus on complex data structures such as Segment Trees, Fenwik Trees, Binary Indexed Trees, and so on.
- Available resources include: The importance of resources in learning anything cannot be overstated. You’ll need a set of good tutorials that are detailed enough to cover all of the concepts, from fundamental to advanced. You should also have a popular set of questions to put your newfound knowledge to use.
- A Guide: Assume you have figured out all three of the preceding points. You know what you want to learn, why you want to learn it, and you have all of the resources and tutorials you need to do so. However, you are still perplexed about many issues, such as “Where to Begin?” and “How to Begin?” So you’ll need someone to walk you through the steps. That is, someone must be present to assist you in making efficient use of the resources available.
This article will introduce top resources sourcing the best way to learn Data Structures and Algorithms. Here you go!
Top Data Structures and Algorithms Learning Resources
Geekster’s DSA online course is specifically designed for learners, whether students or working professionals, who want to learn advanced Data Structures and Algorithms concepts.
It is a course in the design, implementation, and analysis of data structures using the Java programming language.
This holistic course comes under full stack development and will teach you the fundamental data structures such as an array, linked list, binary tree, Stack, and Queue to an advanced level.
With their DSA course, you can prepare for interviews at top-tier product-based companies.
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W3Schools – Algorithms and Data Structures Blog
The first item on the list is a series of blog articles at W3Schools, a popular free site for learning the concepts.
Because the algorithms are mostly taught in C++, we recommend it for those who are intermediate to advanced in this language.
It is entirely self-paced because it is a blog, and you can refer back to it whenever you need a quick refresher. If you are a complete beginner in Data Structures and Algorithms, this may not be a good place to start because the articles read more like summary/revision notes than articles.
These articles are easy to read and well-organized. Also,the text format is easier to digest and learn in some cases.
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FreeCodeCamp – Data Structures from Beginner to Advanced
If you prefer to learn without the pressure of submitting assignments and taking quizzes, freeCodeCamp provides this 8-hour video in which you can learn basic to advanced data structures.
Stacks, linked lists, queues, hash tables, and other concepts will be covered. You will learn how to implement these data structures in Java code because the course is taught in Java. Java intermediate knowledge is required.
While the emphasis of this course is on data structures, you will be introduced to common algorithms such as Kruskal’s Algorithm and hashing algorithms. For beginners to advanced students, the course is simple to follow.
Because it is a video, it is completely free and self-paced, and you can return at any time to review the concepts. So, if you want a more detailed revision with a small time commitment, this might be a better option.
However, keep in mind that watching a video to learn is a passive method of learning, so you will still need to practice the concepts you learn through coding.
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Algorithm Books: A Developer’s Must-Read
Another golden tip for those who believe Algorithms are Data Structures is for those who want to work at Amazon, Google, Facebook, Intel, or Microsoft; remember, aside from UNIX, SQL, and C, it is the only skill that is timeless.
Programming languages come and go, but the core of programming, algorithms and data structures, remains constant.
If you understand how a hash table works, you can use its implementation in any programming language, such as JDK’s HashMap, Python’s Dictionary, or the C++ boost library’s HashMap.
So, if you’re serious about programming and realize that algorithms and data structures aren’t optional, here are some great books to read.
- Introduction to Algorithms, 3rd Edition (The MIT Press)
- Algorithms (4th Edition): Sedgewick, Robert, Wayne, Kevin: 8601419534142: Amazon.com: Books
- The Algorithm Design Manual: Skiena, Steven S S.: 9781849967204: Amazon.com: Books
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Online Data Structures and Algorithms Courses
Here is a list of some of the best free courses for learning data structures and algorithms. Many programmers believe that free resources are bad, which is untrue. Despite the fact that they cannot match the quality and coverage of paid resources for obvious reasons, they are the best resources to begin with.
You can use these web development courses to become acquainted with the essential data structures and to learn the fundamentals. Some of them are particularly useful for interview preparation, so you can use them in addition to any book you are using to prepare for your programming job interview.
- Stack And Queue In Data Structures– From Basics to Advance
- Concepts of Data Structures in C
- Algorithms and Data Structures: Part 1
- Algorithms and Data Structures: Part 2
Data structure and algorithm interview questions: Your answer to get the job
You might be wondering what questions will be asked in your next data structure interview. Remember that data structure interviewers aren’t trying to trick you and don’t expect perfection, but this is their chance to assess your knowledge before investing in your employment. Proper planning is always recommended.
Data structures and algorithm questions are essential components of any programming job interview, particularly one for a Data Science or Java-based role. A solid understanding of data structures and algorithms will help you stand out from the crowd.
The DSA interview questions will give you an idea of the types of questions that may be asked. Although many of these data structure interview questions are expected, you must also invest time in your learning curve. A solid understanding of basic data structures, such as how to access elements from an array or linked list, as well as coding for data science, is essential.
Conclusion
You made it all the way to the end of the article. Best wishes on your programming journey! With the rise of programming and development around the world, learning these has become a lucrative career option.
These are just a few of the many online resources available to help you learn algorithms and data structures. It will not be easy, but by taking these courses, you will be one step closer to mastering data structures and algorithms than others.
