🐍 Python Interview Preparation

Your comprehensive guide to mastering Python for AI/ML interviews

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📖 Introduction

Welcome to my Python prep for AI/ML interviews! 🚀 This repository is your essential guide for mastering Python, the backbone of AI and data science, with hands-on coding and interview-focused practice. From core fundamentals to advanced techniques, it’s crafted to help you shine in technical interviews and AI projects with clarity and confidence.

🌟 What’s Inside?

• Core Python Mastery: Dive deep into data structures, control flow, OOP, and more to ace coding tests.
• AI/ML Libraries: Explore NumPy, Pandas, Matplotlib, Scikit-learn, and other key toolkits.
• Hands-on Practice: Solve curated coding problems with detailed solutions to sharpen your edge.
• Interview Question Bank: Tackle common questions with clear, concise answers.
• Performance Optimization: Learn tips for writing efficient, interview-ready Python code.

🔍 Who Is This For?

• Data Scientists prepping for technical interviews.
• Machine Learning Engineers strengthening Python foundations.
• AI Researchers enhancing coding efficiency.
• Software Engineers transitioning to AI/ML roles.
• Anyone mastering Python for data-centric applications.

🗺️ Comprehensive Learning Roadmap

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🏗️ Core Python Foundations

📊 Data Structures

• Lists
• Dictionaries
• Tuples
• Sets
• Strings
• Frozen Sets

🔄 Control Flow

• If-Else Statements
• Elif Statements
• Nested Conditionals
• For Loops
• While Loops
• Break Statement
• Continue Statement
• Pass Statement

🧩 Functions

• Defining Functions
• Positional Arguments
• Keyword Arguments
• Default Parameters
• Variable-Length Arguments (*args, **kwargs)
• Lambda Expressions
• Recursion
• Function Annotations

🔍 Comprehensions

• List Comprehensions
• Dictionary Comprehensions
• Set Comprehensions
• Generator Expressions

⚠️ Exception Handling

• Try-Except
• Multiple Except Blocks
• Else Clause
• Finally Clause
• Raise Statement
• Custom Exceptions

🧬 Object-Oriented Programming

• Classes and Objects
• Attributes
• Methods
• Inheritance
• Multiple Inheritance
• Encapsulation
• Polymorphism
• Abstract Classes
• Static Methods
• Class Methods

📦 Modules and Packages

• Importing Modules
• Creating Modules
• Packages
• Standard Library
  • math
  • random
  • datetime
  • os
  • sys
  • time

📄 File Handling

• Reading Files
• Writing Files
• CSV Files

🔄 Iterators and Generators

• Iterators
• Generators
• Yield Statement

🎁 Decorators

• Function Decorators
• Class Decorators

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💡 Why Master Python for AI/ML?

Python is the go-to language for AI/ML, and here’s why:

1. Versatility: Powers the full AI workflow—from data cleaning to deployment.
2. Rich Ecosystem: Packed with libraries like NumPy and Scikit-learn.
3. Readability: Clean syntax boosts focus on problem-solving.
4. Industry Demand: A must-have skill for 6 LPA+ AI/ML roles.
5. Community Support: Tap into a huge network of experts.

This repo is my roadmap to mastering Python for technical interviews and AI/ML careers—let’s build that skill set together!

📆 Study Plan

• Week 1-2: Core Python Fundamentals
• Week 3-4: Data Structures and Algorithms

🤝 Contributions

Love to collaborate? Here’s how! 🌟

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/amazing-addition).
3. Commit your changes (git commit -m 'Add some amazing content').
4. Push to the branch (git push origin feature/amazing-addition).
5. Open a Pull Request.

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Happy Learning and Good Luck with Your Interviews! ✨