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A comprehensive resource for Python interview preparation, featuring coding challenges, solutions, and tutorials on core concepts like data structures, algorithms, and libraries. Designed to help developers excel in technical interviews with practical exercises and detailed explanations.

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🐍 Python Interview Preparation

Python Logo NumPy Pandas scikit-learn Matplotlib Seaborn

Your comprehensive guide to mastering Python for AI/ML interviews


📖 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


🏗️ 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

💡 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.

Happy Learning and Good Luck with Your Interviews! ✨

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A comprehensive resource for Python interview preparation, featuring coding challenges, solutions, and tutorials on core concepts like data structures, algorithms, and libraries. Designed to help developers excel in technical interviews with practical exercises and detailed explanations.

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