This work reflects my effort to address the challenge of maintaining consistency in competitive programming practice, which is often difficult to sustain. To tackle this, I organized a small group consisting of peers from previous course offering from RKMVERI who share an interest in competitive programming. We meet biweekly to discuss selected problems based on specific topics using Google Meet. During these sessions, we explore algorithms, design optimal solutions, and submit them on LeetCode to evaluate their time complexity.

I chose Python as the primary language for this activity mainly due to personal preference. Python is widely used in machine learning and deep learning, and its ability to support rapid prototyping makes it especially convenient. It allows us to implement solutions quickly with minimal code, which is well-suited to the goals of this group.

From a career perspective, proficiency in competitive programming and data structures and algorithms is crucial. Whether applying for software development positions or research scientist roles, most industry jobs require a screening process that involves solving such problems. Engaging in these biweekly sessions helps me approach this otherwise mundane task with more motivation and accountability.

Initially, I believed that regular practice in competitive programming would build the kind of muscle memory needed to excel. However, I realized that the problems I will eventually face may differ and may not require the same type of muscle memory to succeed. Nevertheless, these sessions remain valuable, as they provide a structured opportunity to meet, discuss interesting problems, and keep up the practice consistently.