How to Solve Algorithm Problems
How to Solve Algorithm Problems
Make Coding Interview Preparation Less Painful
About the Book
Preparing for coding interviews can often be a daunting task, causing stress and anxiety for many individuals. Several factors contribute to this feeling:
- Scattered and overwhelming information: The abundance of resources available, including online tutorials, blog posts, and coding platforms, can make it difficult to know where to start or which materials to focus on. The sheer volume of information can be overwhelming and make the preparation process feel disorganized.
- Lack of clarity in the coding interview process: The interview process itself may lack clear guidelines or a standardized structure. Each company or organization may have its own unique approach, making it challenging to know what specific topics or coding problems to prioritize during preparation. This lack of clarity can add to the uncertainty and stress of the interview preparation phase.
- External biases, such as company and team culture: The culture and values of the company conducting the coding interview, as well as the team you may potentially join, can introduce additional pressure.
As a result, many candidates find themselves on a bumpy road, investing excessive time in solving numerous leetcode problems. This approach often leads to confusion, frustration, wasted time, and missed opportunities to demonstrate their coding skills during interviews.
It's crucial to move beyond solely solving leetcode problems and adopt a new approach to your preparation that emphasizes studying algorithms and data structures effectively.
Introducing "How to Solve Algorithm Problems" a guide written by an experienced programmer and AI expert. This guide is developed to help you improve your approach to solving algorithm problems, write efficient code that impresses your interviewer, and adopt a better preparation framework that makes the journey enjoyable and fun.
What is the goal of this guide?
The goal of our guide is to enable you to:
- Approach solving algorithm problems differently.
- Learn how to write efficient code that impresses your interviewer.
- Adopt a better preparation framework that makes the journey enjoyable and fun.
- Familiarize yourself with the three most crucial algorithm techniques used in problem-solving that enable you to solve 80% of algorithm problems.
What should you expect after completing this guide?
After reading our guide and completing the practice exercises, you will be able to:
- Reduce the time for solving algorithm problems.
- Feel less stressed during coding interviews by using our proposed learning framework.
- Have a better behavioral impression on your coding interviews.
- Develop an optimized version for your proposed algorithm quickly by writing efficient code that impresses your interviewer
Learn Algorithms by Doing: Well-Selected Practice Problems
- Our notion template is designed to make you practice solving algorithm problems in the proper way. In this template, you will find 50 Algorithm Problems: 50 well-selected algorithm problems with different levels of difficulty to ensure you apply the techniques mentioned in this guide.
- A Progress Tracker: To keep you on track and not procrastinate.
- Resources: To provide you with the most effective and comprehensive information and guidance about solving those problems.
Whether you are a student looking to improve your problem-solving skills or a job seeker preparing for your next coding interview, I hope this guide helps you to master algorithms and achieve your goals of becoming a skilled programmer and ace your coding interviews.
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Table of Contents
- GuideBook
- Preface
- How to Solve Algorithm Problems
- Learning Cycle & Interview Assessment Factors
-
Solving Algorithm Problems
-
3.1 Steps to Solve Algorithm Problems
- 3.1.1 Understand the Problem
- 3.1.2 Formalize the Problem
- 3.1.3 Repeat Reading the Question Yourself
- 3.1.4 Bring Input Examples
- 3.1.5 Develop a Brute-Force Solution
- 3.1.6 Analyze Time and Space Complexities For the Brute-Force Solution
- 3.1.7 Optimize The Brute-Force Solution
- 3.1.8 Analyze Time and Space Complexities For the Optimized Solution
- 3.2 KSum Family Problems
-
3.1 Steps to Solve Algorithm Problems
- 4.1. FGCC Framework
- 4.2. FGCC In Practice
- 5. Top #3 Algorithm Techniques
- 6. Supplements
- References
- Acknowledgments
- About the Author
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