About two months ago, I received an unexpected email from Google regarding my job application. Initially, I thought it was spam. However, after a screening call, I learned that I had two online interviews coming up: one technical and one behavioral. This was a big deal for me because Google is known as a top engineering company.

As a software developer with experience in telecommunications, my background focused more on high-level tasks rather than algorithms. My work involved routing and message processing, which didn’t require deep algorithmic knowledge. This left me feeling unprepared for the upcoming interviews.

Creating a Learning Plan

I had only one week to prepare while balancing my day job and other commitments. To make the most of my time, I decided to focus on learning algorithm patterns instead of trying to master everything at once. I knew that understanding common problems would help me during the interviews.

I avoided reading complex algorithm books or watching lengthy videos that could lead to procrastination. Instead, I aimed to identify key concepts that would allow me to tackle problems efficiently during the interview.

Using AI as a Learning Tool

On the first day of my preparation, I decided to use an AI tool as my teacher. By sharing my situation with it, I set clear goals: learn new algorithm concepts without diving into code immediately. The AI helped me solve simple problems like “Best Time to Buy and Sell Stock” and “Valid Anagram.” These successes boosted my confidence.

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This approach allowed me to see how basic data structures could be used cleverly in problem-solving. For instance, using an unordered set helped me understand how certain properties could simplify solutions.

Diving Deeper into Concepts

On the second day, I intensified my learning by tackling more complex problems within strict time limits. This included challenges like “Reverse Linked List” and “Maximum Depth of Binary Tree.” Each problem taught me valuable lessons about lists and trees.

I discovered that many tree problems were similar to previous challenges I’d faced. This realization made them less intimidating and more manageable as I connected them with real-world scenarios from my work experience.

Final Preparations Before the Interview

As the interview date approached, I shifted focus towards medium-level problems since they were more likely to appear during the actual interview. Tasks like “Merge k Sorted Lists” became easier as I applied what I’d learned about algorithms.

I also practiced writing code without compiling it first, which helped simulate real interview conditions. Although this was challenging at times due to potential errors, it forced me to think critically about each line of code before submission.

Key takeaways

• Focus on learning common algorithm patterns for better problem-solving.
• Use AI tools as interactive teachers for personalized learning experiences.
• Tackle medium-level problems closer to your interview date for effective practice.

FAQ

• What was your biggest challenge in preparing for the Google interview?
• How did you use AI tools effectively?
• What resources did you find most helpful?

For the original report, see the source article.