🐍 Python Fundamentals
Basic Python Programming Course
Start your Python journey from scratch — learn variables, data types, loops,
functions, OOP, file handling, and modules with hands-on exercises and real-world
mini-projects.
Tools & Topics Covered
🐍 Python 3.x
💻 VS Code / PyCharm
📦 pip & venv
📋 Lists, Tuples, Dicts, Sets
🔧 Functions & Lambda
🧱 OOP Concepts
📂 File I/O
⚠️ Exception Handling
📦 Modules & Packages
🏪 Standard Library
🧪 Unit Testing (unittest)
📊 Jupyter Notebook
Course Summary
| Course Name |
Basic Python Programming |
| Duration |
30 Hours (Online / Classroom) |
| Total Modules |
10 Modules |
| Prerequisites |
No prior programming experience required |
| Target Audience |
Beginners, students, non-developers, and professionals switching to tech |
| Certificate |
Yes — Industry-recognised certificate upon completion |
| Mode |
Online & Classroom — with recorded sessions for lifetime access |
📋 Detailed Course Syllabus
🟣 Getting Started
- What is Python? — history, features, and why Python is popular
- Installing Python 3.x and setting up VS Code / PyCharm
- Python interpreter, IDLE, and running your first script
- Interactive mode vs script mode
- Understanding
print(), input(), and comments
- Python indentation and syntax rules
- pip and virtual environments —
venv setup
- Variables and dynamic typing —
int, float, str, bool, None
- Type conversion:
int(), float(), str(), bool()
- Arithmetic, comparison, logical, bitwise, and assignment operators
- String operations — concatenation, repetition, slicing,
f-strings
- String methods:
upper(), lower(), strip(), split(), replace(), find()
- Working with
input() and user input validation
🟡 Control Flow & Data Structures
- Conditional statements:
if, elif, else
- Nested conditions and ternary expressions
for loop — iterating over sequences and rangeswhile loop — condition-based iterationbreak, continue, pass statementsrange() function and loop patterns- Nested loops and loop-else clauses
- Lists — creation, indexing, slicing, CRUD methods, list comprehensions
- Tuples — immutability, packing/unpacking, named tuples
- Sets — unique elements, union, intersection, difference
- Dictionaries — key-value pairs, CRUD operations,
keys(), values(), items()
- Nested data structures — list of dicts, dict of lists
- List, dict, and set comprehensions
sorted(), enumerate(), zip(), map(), filter()
🟢 Functions & Modules
- Defining and calling functions —
def, parameters, return values
- Default arguments, keyword arguments,
*args, **kwargs
- Scope — local, global, nonlocal variables
- Lambda (anonymous) functions — syntax and use cases
- Higher-order functions: passing functions as arguments
- Recursion — base case, recursive case, factorial / Fibonacci examples
- Docstrings and function annotations
- Importing modules —
import, from ... import, aliases
- Creating your own module and reusing code across files
- Python Standard Library highlights:
math, random, datetime, os, sys, json, re
- Installing third-party packages with pip:
pip install requests
- Package structure —
__init__.py, sub-packages
if __name__ == "__main__" pattern
🟠 OOP & File Handling
- Classes and objects —
class, __init__, self
- Instance variables vs class variables
- Instance methods, class methods (
@classmethod), static methods (@staticmethod)
- Inheritance — single, multilevel,
super()
- Encapsulation — public, protected (
_), private (__) attributes
- Polymorphism — method overriding, duck typing
- Magic / dunder methods:
__str__, __repr__, __len__, __eq__
- Reading and writing text files —
open(), read(), write(), readlines()
- Context managers —
with open(...) as f:
- Working with CSV files using the
csv module
- JSON serialization —
json.dumps(), json.loads(), json.load(), json.dump()
- Exception handling —
try, except, else, finally
- Catching specific exceptions vs bare
except
- Raising exceptions —
raise, custom exception classes
🟥 Advanced Basics & Projects
- Iterators —
__iter__, __next__, iter(), next()
- Generators —
yield keyword, generator expressions
- Useful built-ins:
sorted(), reversed(), any(), all(), min(), max(), sum()
- Decorators — introduction, writing a simple logging decorator
- Context managers with
contextlib
- Unit testing with
unittest — test cases, assertions, test runner
📦 Project Options:
- Student Marks Calculator — input, loops, functions, file output
- Simple Contact Book — dict-based CRUD, JSON persistence
- Number Guessing Game — random, loops, input validation
- CSV Data Analyser — read CSV, compute stats, display report
✅ Skills Demonstrated:
- Functions and OOP
- File I/O and JSON
- Error handling
- Clean code and docstrings
- Unit tests for core functions
