Best Ways To Learn Data Structures And Algorithms
You may overhear people saying, “It’s important to master Data Structures and Algorithms.” But have you ever thought about why you should have a good command of Data Structures and Algorithms?
Data Structures and Algorithms help us solve real-world problems. For example, while developing a website, you might have to use a binary tree to get the hierarchy of your web pages.
Due to its utmost importance in companies, engineering college grads and working professionals can’t skip DSA.
Luckily, students get more reality checks from their seniors or platforms like LinkedIn. Even before entering the real world of job-hunting or the workplace. Almost every tech-giants like Amazon, Google, Microsoft, and Adobe conduct multiple interviews to evaluate applicants’ problem-solving skills and knowledge of data structures and algorithms.
After knowing its importance, you might seek the best way to learn data structures and algorithms.
Don’t worry; today’s article will clear all the confusion and guide you to the best way to learn data structures and algorithms.
Let’s get started with a strategic plan to make your learning more efficient and convenient.
1. Look Out For Best Resources:
In this era of the internet, you can find countless resources such as paid or unpaid video lectures, tutorials, articles, books etc. Yet, it is quite a daunting task to find relevant material.
Due to lack of guidance, students often encounter inadequate learning resources that do not make them proficient in Data Structures and Algorithms. Instead, they kill their interest and curiosity in the subject.
Therefore, students should choose a reliable platform where they can watch video lectures to begin learning data structures and algorithms and take their skill assessments within frequent intervals.
You might be thinking about buying books, but these books may not be the best way to learn data structures and algorithms.
The more we write code, the more we learn. Although, if you are looking for some good reference books, check out five books to brush up on your concepts on DSA.
Understand the fundamentals properly
What if someone asked you to write a speech in Japanese, but you don’t know Japanese. Will you be able to write? Obviously Not.
Such is the case here. To start working on problems, you have to grasp the knowledge of Fundamental concepts.
So, after collecting the relevant resources, start with the basics.
- Learn how to use each data structure and implement them by hand using any programming language of your choice.
Having doubts about which programming language to choose, watch this.
- Build a strong foundation by acquiring a deep understanding of how each data structure works.
- Learn how to restructure any data structure according to multiple use cases.
- Understand the concept of Time and Space complexity.
- Get into the habit of writing code with pen and paper. It will help in the long run- along with the interviews.
The following is an ordered list of data structures and algorithms you need to master:
- Tuple and Sets
- Lists and Two Dimensional Lists
- HashMap and HashTable
- Linked Lists
- Stack and Queues
- Priority Queues
- Dynamic Programming
3. Increase your Problem-Solving Ability
After finding relevant resources, you have learnt DSA. What about the number of problems that we need to solve before we can say we are good with Data structures.
One can generally have questions like “How many questions do I need to practice? How much time should I invest in solving a problem?”
Well, we have one line for all those struggling learners: “Focus on Quality over Quantity”. First, choose a data structure and solve 15 easy problems, then 10 medium-level problems and at least five difficult problems.
There are no limitations on the number of questions, but levelling up from easy to hard problems will help you strengthen your concepts. Once you start solving problems, some days you will solve them in one go while getting stuck on other days.
It’s alright. Try that problem utmost for two hours using pen and paper.
“Great job,” if you get it. If not, try it again. Still not; please don’t lose hope. It’s normal and happens with everyone eager to learn. Now watch the solution, dry-run it, examine what points you were missing and code it.
Remember to bookmark the problems that you could not solve in one go. Then, come back after 15-20 days and try to solve the same problem again.
4. Spaced Repetition
“I’ve solved a lot of problems but still can’t solve them when someone asks me unexpectedly or a week later. How am I going to remember them?”
Honestly, by cramming up the codes, all you are doing is making the situation worse and losing everything you have learned so far.
The key to solving any problem is practice and spaced repetition. Spaced repetition is a memory method that involves reviewing and recalling concepts at ideal spacing intervals until it is fully learnt.
The best way is to solve the problem after four days. Then in 10 days, then in a month. It will eventually become a habit for you to revise the concepts at ideal spacing intervals.
5. Practice More and More
Till now, we have already learnt DSA. To move from being good to being among the best. Practice is the key.
So now, after one to two months of regular learning to code, you should start practising — a lot! Try to solve more questions on different websites to reach the advanced level.
Many interactive websites focus heavily on your practice by providing you with countless questions and coding contests.
Coding contests are the most reliable way to upgrade yourself. They are like a sports field where you challenge yourself and get the better of others.
Confused about how to get started with coding competitions? Read this blog.
6. Notice the patterns
Once you solve plenty of problems, you will begin to notice patterns.
Yes, you read that correctly.
You have already solved enough problems for almost all the topics. Solving new problems would be a subset or combination of already learnt concepts. You will realise that most of the logic and code is common among them and can be reused depending on use cases.
The smart move you can take here is to isolate your common code and practice it more often. You may wonder why we need this.
But the benefits of isolating techniques that are reused are:
- You will be able to code it in one go, which shows you have a good hold on implementing data structures.
- You can code it without giving any compiling or runtime errors.
- You can restructure the code to new problems quickly.
7. It’s time for Interview Problems
A college student’s ultimate goal is to get a job by the end of their final year.
Every other company, either fast-growing startups or product-based companies like Google, Microsoft, Amazon, Facebook, will undoubtedly test your knowledge and problem-solving skills.
Don’t worry! If you have followed the path as stated above, we can undoubtedly say that you’ve learned data structures because:
- You know the fundamentals of data structures and algorithms.
- You know the core implementation of each data structure along with its implementation and all the method calls.
- You would have practised around 300 to 400 problems with varying difficulty levels.
- You would have taught the habit of revising the concepts after an ideal interval of time.
- You know the common codes which can be reused depending on the use cases.
Now, All you have to do is skim through the core set and practice standard questions company-wise on different topics.
Why choose Coding Ninjas?
Well, you must be wondering what‘s so special about Coding Ninjas? Coding Ninjas’ courses are an investment for upskilling yourself!
We urge you to explore the courses on our platform Coding Ninjas and there will be no turning back.
After completing the course, Coding Ninjas provides Internships and Job opportunities in various companies, including Coding Ninjas itself.
Furthermore, we have CodeStudio – one of the best platforms created by aspiring and creative minds, providing you with 2115 DSA problems frequently asked in interview rounds.
In short, Coding Ninjas will be for sure the best way to learn data structures and algorithms. It has hassle-free, adaptive and excelling online courses, mentors support, blogs, Interview-Experiences and everything you need to become the perfect candidate for your dream company!
Therefore, if you are interested in any of the courses provided by Coding Ninjas, don’t think much. Just go for it and trust me- you won’t regret your decision!
Let’s proceed to know students’ frequently asked questions regarding how to practice data structures and algorithms.
Frequently Asked Questions
How to start with data structures and algorithms?
1. Look out for the best resources to learn the basics.
2. Start implementing each data structure.
3. Understand the internal workings of each data structure.
4. Practice easy, medium and hard questions.
5. Notice the patterns in problems and isolate the standard codes.
From where to learn data structures?
Coding Ninjas provide hassle-free, adaptive, online courses along with mentors and teaching assistants.
How long does it take to master data structures and algorithms?
It depends on the individual’s learning style. Usually, it takes 2-3 months to learn the basics and then a rigorous, six months regular practice of questions to master data structures and algorithms.
How many CodeStudio questions should I do a day?
Practice 5-6 questions a day with consistency until you get a good hold on problems.
Which language is best for data structure?
Are data structures important for placements?
Data structure and algorithms are essential for getting a placement as it helps one solve programming-related problems and help us in cracking campus placements in no time.
Why are data structures hard?
No, data structures are not hard. It just takes your regular practice to master data structures.
This blog briefly explains the best way to learn data structures and algorithms.
We presented a well-thought-out seven-step plan that one could follow irrespective of their branch, experience, prior knowledge, etc. It will help you lay a solid foundation in data structures and algorithms and successfully pass technical interviews.