Learn Python from scratch — one concept at a time, with runnable code you can type and run yourself. This course focuses on logic building, not memorising syntax. By the end, you will write real programs, handle files, build small projects, and understand object-oriented programming. No prior programming experience needed.
Class 9–12 and BCA/BSc/BTech students who want to build strong programming fundamentals for future study or placements.
Working professionals moving toward automation, scripting, or software development, starting from zero.
You already work with data and want to add Python automation and scripting to your skillset.
Anyone who has wanted to learn programming but found other courses too fast, too theoretical, or too intimidating.
Ten modules, each with runnable code examples you write and run yourself.
| Module | Topics Covered | What You Write |
|---|---|---|
| 1. Getting Started | Installing Python 3.x, IDLE vs VS Code, first program, print(), comments, errors | Print statements, greeting programs |
| 2. Variables & Data Types | int, float, str, bool, type conversion, input(), f-strings | Simple calculator, age calculator |
| 3. Operators | Arithmetic, comparison, logical, assignment, precedence | Bill splitter, even/odd checker |
| 4. Conditional Logic | if, elif, else, nested conditions, truthy/falsy values | Grade calculator, login check, discount logic |
| 5. Loops | for, while, range(), break, continue, else with loops, nested loops | Multiplication table, number guessing game, pattern printing |
| 6. Collections | Lists, tuples, sets, dictionaries — methods, iteration, comprehensions | To-do list, word frequency counter, student marks dictionary |
| 7. Functions | Defining functions, arguments, default arguments, *args/**kwargs, return values, scope | Reusable calculator functions, modular code |
| 8. Exception Handling | try/except/else/finally, common exceptions, raising exceptions | Input validation that never crashes |
| 9. File Handling | Opening files, read/write/append modes, with statement, CSV basics | Save and load a to-do list from a file |
| 10. Object-Oriented Programming | Classes, objects, __init__, methods, inheritance, basic encapsulation | Bank account class, student class with methods |
NumPy / Pandas — introduced only if the batch curriculum includes them. [VERIFY]
Web framework overview (Flask) — brief introduction only, if included. [VERIFY]
Duration: Contact us for the current schedule.
Every code block below is runnable Python 3.x. You will type these yourself, run them, and modify them.
In the final weeks, you build one complete project that ties everything together. Choose from these options.
Add, view, search, update, and delete student records. Store data in a CSV file. Uses classes, functions, file handling, exception handling, and loops. Most popular project choice.
A calculator that performs arithmetic operations and saves the calculation history to a file. Uses functions, exception handling, and file I/O. Good for beginners.
Add, complete, delete, and list tasks. Save tasks to a file so they persist between runs. Uses lists, dictionaries, file handling, and loops.
Record expenses by category, view totals, and export a monthly summary. Uses dictionaries, file I/O, and basic data analysis. Good bridge to data work.
[]. A tuple is immutable — once created, its elements cannot be changed, and it uses parentheses (). Tuples are faster and are used when the data should not change (like coordinates or configuration constants).== compares values — do two objects hold the same data. is compares identity — do two variables point to the same object in memory. Example: [1,2] == [1,2] is True, but [1,2] is [1,2] is False because they are different objects.*args allows a function to accept any number of positional arguments as a tuple. **kwargs allows any number of keyword arguments as a dictionary. Example: def f(*args, **kwargs) can be called as f(1, 2, name="Rahul").copy.copy() for shallow and copy.deepcopy() for deep.__init__ is the constructor method of a class. It runs automatically when an object is created and is used to initialise the object's attributes. Example: def __init__(self, name): self.name = name.self (the instance) as the first parameter (unless they are static or class methods).try, except, else, and finally blocks to catch and handle runtime errors gracefully instead of crashing the program. Example: converting user input to a number can raise a ValueError — handling it lets you ask again instead of crashing.xrange() existed only in Python 2 and returned an iterator. In Python 3, range() behaves like Python 2's xrange() — it returns a lazy sequence, not a full list. xrange() is no longer used.square = lambda x: x * x. Useful when you need a short function for a moment, often with map(), filter(), or sorting. Not meant for complex logic — use def for that.append(x) adds a single element x at the end — even if x is a list, the whole list becomes one element. extend(iterable) adds each element of the iterable individually. Example: [1,2].append([3,4]) gives [1,2,[3,4]]; [1,2].extend([3,4]) gives [1,2,3,4].Choose Python if your goal is programming, automation, scripting, software development, or logic building. Choose Data Analytics if your goal is reporting, dashboards, and SQL. If you want both, do Python first, then Data Analytics.
Not strictly required — the lab has systems. But students who practise at home progress faster. Python is free to install on Windows, Mac, or Linux. The instructor will help you install it. [VERIFY WHETHER LAPTOP PRACTICE IS RECOMMENDED]
Yes. Python is used in BCA, BSc IT, BTech, and BCom (data) programmes. If you are in Class 11 or 12 with Computer Science, this course strengthens your fundamentals. It is useful for school projects and later college coursework.
See the teaching style, run your first Python program, and decide whether this is the right starting point for you.
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