🚀 Roadmap to Master Python Programming 🔰

📂 Python Fundamentals
 ∟📂 Learn Syntax, Variables & Data Types
  ∟📂 Master Control Flow & Functions
   ∟📂 Practice with Simple Projects

📂 Intermediate Concepts
 ∟📂 Object-Oriented Programming (OOP)
  ∟📂 Work with Modules & Packages
   ∟📂 Understand Exception Handling & File I/O

📂 Data Structures & Algorithms
 ∟📂 Lists, Tuples, Dictionaries & Sets
  ∟📂 Algorithms & Problem Solving
   ∟📂 Master Recursion & Iteration

📂 Python Libraries & Tools
 ∟📂 Get Comfortable with Pip & Virtual Environments
  ∟📂 Learn NumPy & Pandas for Data Handling
   ∟📂 Explore Matplotlib & Seaborn for Visualization

📂 Web Development with Python
 ∟📂 Understand Flask & Django Frameworks
  ∟📂 Build RESTful APIs
   ∟📂 Integrate Front-End & Back-End

📂 Advanced Topics
 ∟📂 Concurrency: Threads & Asyncio
  ∟📂 Learn Testing with PyTest
   ∟📂 Dive into Design Patterns

📂 Projects & Real-World Applications
 ∟📂 Build Command-Line Tools & Scripts
  ∟📂 Contribute to Open-Source
   ∟📂 Showcase on GitHub & Portfolio

📂 Interview Preparation & Job Hunting
 ∟📂 Solve Python Coding Challenges
  ∟📂 Master Data Structures & Algorithms Interviews
   ∟📂 Network & Apply for Python Roles

✅️ Happy Coding

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Clean code advice for Python:

Do not add redundant context.
Avoid adding unnecessary data to variable names, especially when working with classes.

Example:

This is bad:

class Person:
    def __init__(self, person_first_name, person_last_name, person_age):
        self.person_first_name = person_first_name
        self.person_last_name = person_last_name
        self.person_age = person_age

This is good:

class Person:
    def __init__(self, first_name, last_name, age):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age

Important Python Functions ✅

🚀 Learn API development with Python

🔑 Core Skills Before API Development

Python Fundamentals
- Functions, classes, error handling
- JSON handling (json module)
- Virtual environments (venv, pipenv, or poetry)

HTTP Basics
- What is an API? (REST, GraphQL, gRPC basics)
- HTTP methods: GET, POST, PUT, PATCH, DELETE
- Status codes: 200, 201, 400, 401, 404, 500


🛠️ API Development with Python

1. Frameworks
- Flask (lightweight, easy for beginners)
- FastAPI (modern, async, automatic docs with Swagger/OpenAPI – highly recommended)
- Django REST Framework (DRF) (for large apps with Django)
👉 Start with FastAPI if your goal is modern, production-ready APIs.

2. Core Concepts
- Routing (endpoints like /users, /products)
- Path & query parameters
- Request & response handling (JSON input/output)
- Middleware (logging, authentication, error handling)


3. Data & Persistence
- Working with databases:
- SQL (PostgreSQL, MySQL, SQLite)
- ORMs: SQLAlchemy or Django ORM
- CRUD operations with database integration


4. Authentication & Security
- JWT (JSON Web Tokens)
- OAuth2 (Google, GitHub login)
- API key-based authentication
- CORS handling


5. Testing & Documentation
- Writing tests with pytest or unittest
- Automatic API docs (FastAPI auto-generates Swagger UI)
- Postman or cURL for testing endpoints


6. Deployment & Scaling
- Running APIs with Uvicorn or Gunicorn
- Containerization with Docker
- CI/CD (GitHub Actions, GitLab CI)
- Cloud deployment (AWS, GCP, Azure, or Heroku)


📚 Suggested Learning Path:
Learn FastAPI → build a simple "To-Do API"
Connect a database → PostgreSQL + SQLAlchemy
Add authentication → JWT-based login
Write tests → pytest for endpoints
Deploy on Docker + Cloud

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✅10 Most Useful SQL Interview Queries (with Examples) 💼

1️⃣ Find the second highest salary:

SELECT MAX(salary)  
FROM employees  
WHERE salary < (SELECT MAX(salary) FROM employees);

2️⃣ Count employees in each department:

SELECT department, COUNT(*)  
FROM employees  
GROUP BY department;

3️⃣ Fetch duplicate emails:

SELECT email, COUNT(*)  
FROM users  
GROUP BY email  
HAVING COUNT(*) > 1;

4️⃣ Join orders with customer names:

SELECT c.name, o.order_date  
FROM customers c  
JOIN orders o ON c.id = o.customer_id;

5️⃣ Get top 3 highest salaries:

SELECT DISTINCT salary  
FROM employees  
ORDER BY salary DESC  
LIMIT 3;

6️⃣ Retrieve latest 5 logins:

SELECT * FROM logins  
ORDER BY login_time DESC  
LIMIT 5;

7️⃣ Employees with no manager:

SELECT name  
FROM employees  
WHERE manager_id IS NULL;

8️⃣ Search names starting with ‘S’:

SELECT * FROM employees  
WHERE name LIKE 'S%';

9️⃣ Total sales per month:

SELECT MONTH(order_date) AS month, SUM(amount)  
FROM sales  
GROUP BY MONTH(order_date);

🔟 Delete inactive users:

DELETE FROM users  
WHERE last_active < '2023-01-01';

✅ Tip: Master subqueries, joins, groupings & filters – they show up in nearly every interview!

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This will be a week-by-week series designed to make you interview-ready — covering core concepts, coding questions, and real interview scenarios asked by top companies.

Here’s what’s coming your way 👇

🔹 Week 1: Python Fundamentals (Beginner Level)
• Data types, variables & operators
• If-else, loops & functions
• Input/output & basic problem-solving
💡 *Practice:* Reverse string, Prime check, Factorial, Palindrome

🔹 Week 2: Data Structures in Python
• Lists, Tuples, Sets, Dictionaries
• Comprehensions (list, dict, set)
• Sorting, searching, and nested structures
💡 *Practice:* Frequency count, remove duplicates, find max/min

🔹 Week 3: Functions, Modules & File Handling
• *args, *kwargs, lambda, map/filter/reduce
• File read/write, CSV handling
• Modules & imports
💡 *Practice:* Create custom functions, read data files, handle errors

🔹 Week 4: Object-Oriented Programming (OOP)
• Classes, objects, inheritance, polymorphism
• Encapsulation & abstraction
• Magic methods (__init__, __str__)
💡 *Practice:* Build a simple class like BankAccount or StudentSystem

🔹 Week 5: Exception Handling & Logging
• try-except-else-finally
• Custom exceptions
• Logging errors & debugging best practices
💡 *Practice:* File operations with proper error handling

🔹 Week 6: Advanced Python Concepts
• Decorators, generators, iterators
• Closures & context managers
• Shallow vs deep copy
💡 *Practice:* Create your own decorator, generator examples

🔹 Week 7: Pandas & NumPy for Data Analysis
• DataFrame basics, filtering & grouping
• Handling missing data
• NumPy arrays, slicing, and aggregation
💡 *Practice:* Analyze small CSV datasets

🔹 Week 8: Python for Analytics & Visualization
• Matplotlib, Seaborn basics
• Data summarization & correlation
• Building simple dashboards
💡 *Practice:* Visualize sales or user data

🔹 Week 9: Real Interview Questions (Intermediate–Advanced)
• 50+ Python interview questions with answers
• Common logical & coding tasks
• Real company-style questions (Infosys, TCS, Deloitte, etc.)
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✅ Artificial Intelligence Engineer Roadmap 🤖🧠

🚀 Foundations
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• Probability & Statistics
- Programming
• Python (core language)
• C++ (for performance)
• SQL (for data handling)
- Computer Science Basics
• Data Structures & Algorithms
• OOP Concepts

📘 Core AI Concepts
- Search Algorithms
• BFS, DFS, A*
- Knowledge Representation
• Ontologies, Graphs
- Logic & Reasoning
• Propositional & Predicate Logic
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• Markov Decision Process (MDP)
• Game Theory Basics

🧠 Machine Learning & Deep Learning
- ML Algorithms
• Regression, Classification, Clustering
- Deep Learning
• Neural Networks, CNN, RNN
• Transformers, Attention Mechanisms
- Frameworks
• TensorFlow, PyTorch, Keras

📊 NLP & Computer Vision
- NLP
• Tokenization, Lemmatization
• Language Models (BERT, )
- CV
• Image Classification, Object Detection
• OpenCV, YOLO, Mask R-CNN

🛠 Tools & Platforms
- Jupyter, GitHub, Docker
- MLflow, Weights & Biases
- Hugging Face, OpenAI APIs

☁️ Model Deployment & Monitoring
- FastAPI, Flask for APIs
- CI/CD Pipelines
- Cloud (AWS Sagemaker, GCP Vertex AI, Azure ML)

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- AI Product Thinking
- Explainable AI (XAI)
- Ethics, Bias & Fairness
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