Problem Solving with Python is a structured repository focused on mastering Python programming, logical reasoning, and Data Structures & Algorithms (DSA) through well-implemented problem solutions.
The repository emphasizes clarity, readability, and correctness, making it suitable for technical interview preparation, academic reinforcement, and professional upskilling. Every solution highlights a concept-first approach, ensuring learners understand why a solution works, not just how.
This repository aims to:
- Build strong problem-solving and analytical thinking skills
- Reinforce Python fundamentals through applied examples
- Bridge theoretical computer science concepts with practical implementation
- Serve as a reference for technical interview preparation
- Promote learning through clear explanations and clean code
All implementations adhere to industry standards:
- Consistent and readable coding style
- Maintainable and scalable Python solutions
- Concept-first problem-solving methodology
- Alignment with software engineering and AI-focused interview expectations
The content prepares candidates to:
- Explain reasoning behind algorithmic and data structure choices
- Discuss trade-offs in efficiency, complexity, and scalability
- Analyze time and space complexity critically
- Communicate solutions clearly under interview conditions
Effective explanation of solutions is as critical as coding ability in professional interviews.
Mansoor Bukhari
Bachelor of Science in Artificial Intelligence
GitHub: https://github.com/cyberfantics
This project is licensed under the MIT License. You are free to use, modify, and distribute the repository with proper attribution.