Python Programming

Python Programming
₹1,000₹1,500
60 mins
One-To-One Session

“From beginner to pro—Python grows with you.”


Learn Python Programming from basics to advanced concepts, suitable for beginners, students, and professionals. Understand core Python features such as syntax, data types, loops, functions, and object-oriented programming, along with practical skills like data handling, automation, and visualization using libraries such as NumPy, Pandas, and Matplotlib. Hands-on practice helps you build real-world projects with confidence.


🐍 Python Language Learning Roadmap

📘Step 1: Python Basics

  1. What is Python and where it is used
  2. Installing Python and using IDEs (VS Code, Jupyter)
  3. Python syntax and indentation
  4. Variables and data types
  5. Input and output


📘Step 2: Control Flow

  1. Conditional statements (if, elif, else)
  2. Loops (for, while)
  3. Break, continue, pass


📘Step 3: Data Structures

  1. Lists, tuples, sets, dictionaries
  2. Indexing and slicing
  3. Common built-in functions


📘Step 4: Functions and Modules

  1. Defining and calling functions
  2. Arguments and return values
  3. Lambda functions
  4. Importing modules and packages


📘Step 5: Object-Oriented Programming (OOP)

  1. Classes and objects
  2. Constructors
  3. Inheritance
  4. Polymorphism and encapsulation


📘Step 6: File Handling and Exceptions

  1. Reading and writing files
  2. Working with CSV and text files
  3. Exception handling (try, except, finally)


📘Step 7: Python Libraries (Core)

  1. NumPy (numerical computing)
  2. Pandas (data handling)
  3. Matplotlib & Seaborn (visualization)


📘Step 8: Practical Applications

  1. Data analysis projects
  2. Data cleaning and preprocessing
  3. File handling and report generation
  4. Statistical analysis


📘Step 9: Advanced Python

  1. List comprehensions
  2. Generators and iterators
  3. Decorators
  4. Regular expressions


📘Step 10: Specialized Tracks (Choose One)

  1. Data Science & Machine Learning
  2. Computer Vision with OpenCV
  3. Financial data analysis
  4. Financial Analysis & Quantitative Finance
  5. Deep Learning & AI
  6. Mathematics using Python
  7. Statistics & Probability using Python
  8. Data Visualization & Dashboards


📘Step 11: Projects & Practice

  1. Mini projects
  2. Real-world datasets
  3. Code optimization and debugging


📘Step 12: Version Control & Best Practices

  1. Git and GitHub
  2. Writing clean and efficient code
  3. Documentation and testing



❓Invitee Questions (Python Programming)

🔹Question 1: What topics or skills would you like to focus on during this Python session?

(e.g., basics, data handling, automation, or projects)

🔹Question 2: What is your current experience level in Python?

(Beginner, Intermediate, Advanced)

🔹Question 3: Are you interested in Python for data analysis, web development, automation, or general programming?

🔹Question 4: Do you have any specific projects, assignments, or challenges you want help with?

🔹Question 5: Which Python libraries or tools are you most interested in learning?

(e.g., NumPy, Pandas, Matplotlib... etc.)

🔹Question 6: Is this session for academic support, career development, or personal learning?

🔹Question 7: Do you prefer a theory-focused session, a hands-on coding session, or both?

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