How can you quickly learn data structures and algorithms? (2024)

I can say from personal experience after working with different languages (high and low level) like Golang (during my time at Forward Health), Python (Solved 700 Leetcode problems), C++ (in Operating Systems Course at NYU) and Java (during my internship at AWS) - Python is a definitely a better choice if you are new to programming.Reasons for choosing Python:1. Very Easy to comprehend, almost close to pseudo-code2. Easy to debug. The compilation and run-time errors are informative and intuitive.3. All the Machine Learning, Data Science and Data Engineering jobs need Python.4. Backend web development frameworks like Django and Flask are in Python5. Great community support since it's battle-tested.Python is always a great investment!

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Strategies one can follow to choose a programming language: 1. Candidates usually have the flexibility to choose their preferred programming language. Selecting a language you are proficient in is crucial to avoid the intricacies of unfamiliar languages and to focus on creating efficient data structures for the problem at hand. Reviewing job descriptions and confirming language requirements with recruiters is essential. For beginners, I personally recommend Python and Java due to their simple syntax and extensive libraries, and refreshing or acquiring knowledge of various programming concepts is vital.2. Consistent Practice with Data Structures and Algorithms in chosen language3. Learn how to test your code in your chosen language

When you start learning DSA, the most important thing is consistency. To give a head start- Pick up a language of choice and start learning the fundamentals of Arrays, String, LinkedList, Trees, Stack/Queues, Hashing, and Graphs. - Pick any platform like LeetCode, HackerRank, etc., and start solving easy/medium/hard problems in 10/8/5 numbers. While solving, first try to solve up to a certain time like 20-30 mins, and then look for hints/solutions.- This will give an insight into internal working and patterns on when to use what.- Do the same for algo patterns like DP, Binary Search, Greedy, DAC, etc.Doing this, one would have solved 200+ problems which is enough to build a good knowledge base and tackle most of the coding problems.

Start with easiest DS(like array, list) and move towards complex ones(tree, graph). There are many resources to learn a particular DS. My approach is have a first round with an easy to learn source(popular book, free/paid course). It will be easy to grasp. Although it will not discuss internal and advanced concepts but it will give you basic understanding. Now solve few easy problems on leetcode/hackerrank etc. Next step is revise the same DS using an specialized resource that will cover all the advanced concepts about this. After this learn all the algorithms and patterns related to that DS. Now jump on solving problems based on this DS and associated algorithms. I prefer leetcode as I find their testcases more thorough than others.

Most of the people try to implement the solution without understanding the problem. First understand the nitty gritty of that particular data-structure/algorithm, create mind map how you will approach the solution then writing code is cake walk. 🍰

It depends on the goals you have, isn’t needed to know in depth how these data structures are done if you are going to use them just for some operations, many of those are implemented in a library or in the STL. In the other hand if you want to understand the concepts in order to improve and implement some by yourself, you will need to read the paper where it was released, as it is clear enough and any information related is there, you won’t find other quotations or citations than the paper itself in videos or tutorials on the net, and for sure those are really helpful.

Calculate Time and space complexity and measure algorithms efficiency. Use Big O notations to compare the efficiency. Always there is a chance to improve the performance of the algorithms.

Best tip I can give to learn DSA is to simulate again and again. Keep practising until you are pro in that topic, and this is valid in any hard problem you see in life.

Only Practice is not enough. Consistency is what the main ingredient to excel in DSA. Understanding, Recognising the pattern of the question should be kept in mind while solving a problem. Think from the perspective of the person who wrote the question.

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In my experience, this is the best way to learn data structures and algorithms. Leet code, courses, projects, anything that gets you writing real solutions to difficult problems. Additionally, learning to break a problem down into parts and solve each part is crucial.

DSA Revision strategies which I follow -- To excel in software engineering interviews, especially with companies like Google, it's crucial to master the syntax of your preferred programming language and solve data structure challenges by practicing coding by hand, focusing on clean, error-free syntax without relying on an IDE. - Keep track of all the questions and progress in some documents like Notion Tracker or flashcards. I personally maintain a tabular journal with the following columns - S.No, Problem, Category - Pattern, Difficulty, and Approach. Revisit, Revise, and Optimise whenever required.- Get a Peer, mentor, or friend to conduct mock interviews, be an accountability partner, or be there for emotional support and motivation.

To solidify data structures and algorithms in iOS, review and revise regularly. Leverage online tools like flashcards for memorization and platforms like LeetCode for feedback and solutions. Offline aids such as notes or diagrams help summarize information. Use personalized methods like peer review or self-evaluation to assess progress. Identifying strengths and weaknesses ensures targeted improvement, fostering continuous growth in iOS development.

Consistency in learning data structures is crucial. Your hard work will be rewarded with more hard work, and eventually, all your concepts will "click", enabling you to understand how different data structures work together. This understanding allows you to seamlessly plug and play with them to solve problems, making informed trade-offs between time and space complexity.LeetCode question of the day is a great way to maintain consistency.

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Learning and unlearning is an iterative approach. Following helped me:- Regularly solving problems on platforms like LeetCode, HackerRank, or GeeksForGeeks is essential, ensuring a deep understanding of the problem before starting to write code. This consistent practice enables the development of skills to dissect larger or ambiguous problems into manageable parts and efficiently manage time between understanding, planning, coding, and testing phases.- Attempting to solve problems without using the auto-suggestion feature is pivotal, as it builds confidence and reduces reliance on such features, although it might seem daunting initially.- Joining a community or getting a mentor or a study buddy helps with motivation and accountability.

For enduring success in iOS development, the learning journey never ends. Stay updated with blogs and podcasts, ensuring you're informed about the latest in data structures and algorithms. Platforms like LeetCode provide diverse challenges, keeping you motivated. Offline resources, like books or journals, offer historical context and insights into the future. Personal strategies such as learning from mentors or teaching others maintain engagement and passion. Continuous learning and improvement are the keys to staying at the forefront of data structures and algorithms in the ever-evolving landscape of iOS development.

Be efficient. If you want to learn quickly and especially revise well then you must be efficient. How to be efficient?1. Be selective. Stick to one or two resources -Don't pick up half a dozen books, tutorials, sites, Playlists & courses. Be selective. Find the best ones as per your language, need & level. Stick to it.2. Find resources in your language only.Shouldn't try to waste time in converting 1 language syntax to another. Better to find resources in your language only.3. Don't spend too much time on a practice problem if you are stuck.Give it 45m max, more than that & it's better to actually read the editorial & learn. Most interviews are 45m only.4. Don't go for college text books except for referencing. Not efficient.

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Apart from technical learnings, it is crucial to prioritize overall health using the following strategies -1. Take regular breaks, recharge, and rejuvenate. Allocate time away from screens to rest your eyes and mind.2. Clearly define work hours and stick to them. Allocate time for hobbies, relaxation, and spending time with loved ones.3. Practice mindfulness, a healthy diet, and physical, mental and emotional fitness. Invest time in personal development and learning to enhance self-esteem and life satisfaction. Learn to reach out for help whenever required.4. Not chase money or brand instead focus on self-development.I believe, maintaining overall health is crucial to sustain high levels of productivity and creativity.