If You Can't Build Logic, You Can't Solve LeetCode Problems

Summary

In this video, the speaker shares their personal journey of struggling with DSA (Data Structures and Algorithms) and offers valuable insights for learners. The focus is on building problem-solving logic through consistent practice, rather than relying on quick solutions. The speaker emphasizes quality over quantity, urging viewers to understand the core concepts and avoid memorization. They also stress the importance of developing debugging skills and avoiding overuse of tools like ChatGPT. With a systematic and brain-straining approach to problem-solving, learners can effectively enhance their skills and succeed in coding interviews.

Takeaways

• 😀 Stop relying on solutions: Build your own logic by practicing more and struggling through problems. Your brain needs exercise like muscles in the gym.
• 😀 Practice over quantity: Focus on solving quality questions, not on completing a long list of problems. This ensures better learning and recognition of patterns.
• 😀 Embrace struggling: It’s important to let your brain struggle through problems to improve logic-building skills. Don’t rely on external aids like solutions too soon.
• 😀 Logic-building is key: Developing a solid understanding of algorithms and data structures comes from thinking through problems yourself, not just memorizing solutions.
• 😀 Stop memorizing solutions: Instead of memorizing answers, aim to understand the underlying patterns and logic. This will help you solve different variations of the same problem.
• 😀 Focus on deep learning, not just speed: Take your time with each problem, reflect on your approach, and don’t rush to finish a set of questions.
• 😀 Don’t rely on cheat tools: Avoid using platforms like ChatGPT too much for solving coding problems, as it hinders real problem-solving skills.
• 😀 Build a systematic study routine: Prioritize structured learning by solving tutorial problems, then move on to more complex sheets or platforms like LeetCode.
• 😀 Practice with different question types: Try a variety of problem types to understand how algorithms apply to different scenarios (e.g., two-pointer technique, dynamic programming).
• 😀 Don’t fall for quick fixes: Completing 200-300 problems may not be the solution. What matters is understanding the concepts behind those problems.

Q & A

Why is it important to stop looking at solutions immediately when stuck on a problem?

It is important because solving problems requires developing your own logic. By constantly looking at solutions, you avoid the mental struggle that helps you build critical problem-solving skills. This struggle is similar to a workout for your brain, helping you grow and enhance your logical abilities.

What role does practice play in building problem-solving logic?

Practice plays a crucial role in building problem-solving logic. The more problems you attempt on your own, the better you understand the patterns and techniques needed to solve them. Initially, it may feel difficult, but with consistent effort, your brain gets better at recognizing solutions.

How does avoiding solutions help in developing a better brain workout?

By avoiding immediate solutions, your brain is forced to think critically and figure out the problem on its own. This mental struggle strengthens your cognitive abilities, much like how physical exercise helps build muscles. The process of struggling and trying to figure things out independently is key to improving brain function.

What should you focus on, quantity or quality, when solving coding problems?

You should focus on the quality of problems rather than quantity. Instead of trying to solve hundreds of questions quickly, focus on understanding the logic behind each question and the techniques used to solve them. This approach helps in recognizing patterns and building a strong foundation in problem-solving.

Why is it better to focus on quality problems instead of solving a large number of problems?

Focusing on quality problems allows you to understand deeper concepts, identify algorithms, and recognize patterns in coding challenges. This results in better retention and application of problem-solving techniques, rather than just memorizing solutions to many problems.

What is the issue with memorizing solutions to coding problems?

Memorizing solutions limits your ability to apply logic to new problems. It makes your brain reliant on predefined answers and prevents you from thinking critically. Instead, understanding the underlying concepts and approaches helps you tackle new and unfamiliar problems effectively.

How can systematic study help in preparing for coding interviews?

Systematic study helps you build a structured approach to learning. It ensures that you cover all necessary topics, such as data structures and algorithms, at the right pace. By following a tutorial, solving related questions, and then gradually progressing to more difficult problems, you develop the skills needed for interviews.

What is the benefit of revising problems regularly in your study process?

Revising problems regularly helps reinforce concepts and ensures that your learning is strong. It allows you to identify areas where you may still struggle, and by revisiting these problems, you can improve your understanding and retention of important techniques.

How can using platforms like ChatGPT for debugging affect your learning?

Using platforms like ChatGPT for debugging can be helpful but may hinder your learning in the long run. Relying too much on external tools prevents you from developing the critical thinking skills required to identify and solve problems on your own. It’s important to try debugging manually before seeking help.

Why should you avoid using ChatGPT for solving coding problems directly?

You should avoid using ChatGPT or similar tools for directly solving coding problems because it can lead to dependency. By solving problems on your own and thinking critically, you develop the skills needed for interviews and real-world coding challenges. ChatGPT can be used for supplementary purposes, but not as the primary tool for solving problems.