Master Python Programming in 30 Days

Basic to Data Science

Who Will Benefit from This Course:

What You’ll Learn?

History and evolution of Python
Features and real-world applications
Installing Python on various OS
Setting up environment variables
Installing IDEs (PyCharm, VS Code)
Installing Jupyter
Using cells, markdown, and basic operations
Code execution and visualization
Declaring and initializing variables
Python keywords and naming conventions
Writing comments and docstrings
Arithmetic, relational, logical, bitwise, assignment, and special operators
Operator precedence
input() and print() functions
Formatting output using format() and f-strings
if, else, elif
Nested conditions and shorthand syntax
for, while loops
break, continue, and pass statements
Numbers, strings, lists, tuples, dictionaries, and sets
Type casting and type checking
Defining and calling functions
Arguments, return values, and scope
*args and **kwargs
Syntax and use cases
Anonymous functions in Pythonic cod
Writing and applying decorators
yield, next() for generator functions
Basics of OOP
__init__() method and instance variables
Inheritance, polymorphism, encapsulation, and abstraction
Method overriding and super()
Reading and writing files
File modes and context manager (with)
try, except, finally, raise, and custom exceptions
re module
Pattern matching, searching, and replacing
Using logging module
Setting log levels
Debugging techniques
Unit testing with unittest
Writing test cases and test suites
Using sys.argv
argparse module for advanced parsing
Connecting with SQLite and MySQL
Executing queries using Python
Basics of REST APIs
Using Flask to build simple APIs
Data models and schema validation
Type hints and data parsing
Overview of NumPy, Pandas, Matplotlib, Seaborn
Basic operations and data visualization
Project problem statement
Data preprocessing, analysis, modeling, and visualization
Model evaluation and final report
Best practices in Python
Code optimization and readability
Preparing for interviews and real-world applications

Click below to download the full course syllabus in PDF format.

Read What Learners Say

I had zero programming knowledge when I joined, but this course made everything easy to understand. The real-life examples and hands-on coding helped me gain confidence

As a marketing professional, I wanted to move into data analysis. This course gave me the Python skills I needed to make that transition. I even landed my first tech job

I loved how each module builds on the previous one. The lessons are clear, and the practice projects really helped me apply what I learned.

I now automate tasks for my clients using Python. The API and automation modules were a game-changer. Thank you for such a practical course

I took this course to improve my programming skills for work. Now I’m contributing to automation and analytics tasks at my company

I was struggling with my final year project until I found this course. The modules on data handling and visualization were exactly what I needed!

What sets this course apart is the hands-on projects. I built a mini data dashboard by the end, which I showcased in my job interview!

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Last Updated:

July 23, 2025 5:35 am

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