Python · Course Overview
Inside Uncodemy's Python Programming Course: What You Learn
Quick summary — what you learn in the Python course
Uncodemy's Python programming course typically covers core syntax, data types, control flow and functions; data structures; object-oriented programming, modules and error handling; working with files, CSV, JSON and APIs; popular libraries; testing basics; and projects you can show employers. Confirm the current official syllabus, duration and fees with a counsellor.
In this guide you will learn:
- The typical modules — and what each covers.
- Example code — from each stage.
- The projects — you build.
- How to confirm — the official syllabus.
- Interview questions — for Python beginners.
SECTION 01Stage 1: Python basics and data structures
The course typically begins with installing Python, running scripts and learning core syntax: variables, data types, operators, conditions, loops and functions. Data structures follow, including lists, tuples, dictionaries and sets, with practice choosing the right one for each problem. This is a typical breakdown; the official module list may differ:
| Module | Key topics | You practise | Why it matters |
|---|---|---|---|
| Getting started | Installing Python, running scripts, input/output | First programs | Comfort with tools |
| Control flow | if/elif/else, for, while | Small decision programs | Logic building |
| Functions | Parameters, return values, scope | Reusable code | Clean, testable code |
| Data structures | Lists, tuples, dicts, sets, comprehensions | Data handling tasks | Used in every program |
def grade(score: int) -> str:
if score >= 90:
return "A"
elif score >= 75:
return "B"
elif score >= 50:
return "C"
return "Needs improvement"
scores = {"Asha": 92, "Ravi": 68, "Meera": 77}
for name, score in scores.items():
print(f"{name:6} {score:3} {grade(score)}")
orders = [
{"id": 1, "city": "Noida", "amount": 450},
{"id": 2, "city": "Delhi", "amount": 1200},
{"id": 3, "city": "Noida", "amount": 300},
]
cities = {o["city"] for o in orders} # set: unique values
totals = {c: sum(o["amount"] for o in orders if o["city"] == c) for c in cities}
big = [o["id"] for o in orders if o["amount"] > 400] # list comprehension
print("cities:", sorted(cities))
print("totals:", totals)
print("big orders:", big)
SECTION 02Stage 2: OOP, modules and error handling
Once basics are comfortable, the course typically moves to organising larger programs. Object-oriented programming introduces classes, objects, methods and inheritance. Modules and packages show how to split code into files and reuse libraries. Error handling with try and except teaches you to deal with bad input and failures gracefully, which is essential for real programs:
| Module | Key topics | You practise | Why it matters |
|---|---|---|---|
| Classes and objects | __init__, attributes, methods | Model real things in code | Organised programs |
| Inheritance | Parent and child classes, super() | Share behaviour | Less repetition |
| Modules and packages | import, virtual environments, pip | Split code into files | Maintainable projects |
| Error handling | try/except/finally, custom exceptions | Handle bad input | Robust programs |
class BankAccount:
def __init__(self, owner: str, balance: float = 0.0):
self.owner = owner
self.balance = balance
def deposit(self, amount: float) -> None:
if amount <= 0:
raise ValueError("deposit must be positive")
self.balance += amount
def withdraw(self, amount: float) -> None:
if amount > self.balance:
raise ValueError("insufficient balance")
self.balance -= amount
class SavingsAccount(BankAccount):
def add_interest(self, rate: float) -> None:
self.balance = round(self.balance * (1 + rate), 2)
acc = SavingsAccount("Asha", 1000)
acc.deposit(500)
acc.add_interest(0.04)
print(acc.owner, acc.balance)
def read_age(text: str) -> int:
try:
age = int(text)
except ValueError:
raise ValueError(f"'{text}' is not a whole number") from None
if not 0 < age < 120:
raise ValueError("age must be between 1 and 119")
return age
for value in ["25", "abc", "150"]:
try:
print(value, "->", read_age(value))
except ValueError as err:
print(value, "-> error:", err)
SECTION 03Stage 3: files, APIs, libraries, testing and projects
Later modules typically apply Python to practical tasks: reading and writing files, CSV and JSON, calling web APIs with the requests library, and using popular libraries for data or automation. Testing basics with pytest show how to check your code automatically. The course then focuses on projects, such as a command-line tool, a file automation script or a small data report, along with Git and interview preparation. Confirm exact topics with a counsellor:
| Module | Key topics | You build | Why it matters |
|---|---|---|---|
| Files and formats | open, csv, json, pathlib | File processing scripts | Automate everyday tasks |
| APIs | requests, status codes, JSON | A script calling a public API | Connect to services |
| Testing | pytest, assertions, fixtures | Tests for your functions | Trustworthy code |
| Projects | Planning, Git, README | Two or three portfolio projects | Proof of skills |
import csv
import json
from pathlib import Path
Path("students.csv").write_text("name,score\nAsha,92\nRavi,68\nMeera,77\n")
with open("students.csv", newline="") as f:
rows = list(csv.DictReader(f))
report = {
"count": len(rows),
"average": round(sum(int(r["score"]) for r in rows) / len(rows), 1),
"top": max(rows, key=lambda r: int(r["score"]))["name"],
}
Path("report.json").write_text(json.dumps(report, indent=2))
print(report)
# test_grades.py Run: pytest -q
import pytest
def grade(score: int) -> str:
if not 0 <= score <= 100:
raise ValueError("score must be 0-100")
return "A" if score >= 90 else "B" if score >= 75 else "C" if score >= 50 else "F"
@pytest.mark.parametrize("score,expected", [(95, "A"), (75, "B"), (50, "C"), (10, "F")])
def test_grade(score, expected):
assert grade(score) == expected
def test_invalid_score():
with pytest.raises(ValueError):
grade(101)
SECTION 04How to confirm the syllabus and plan your study
Use these templates to check details and track your progress:
1. Can I see the current official Python syllabus?
2. How long is the course, and what are the batch timings?
3. How much time is hands-on coding?
4. Which projects are included, and are they reviewed?
5. Are files, APIs, testing and Git covered?
6. What comes after this course (data, web, automation)?
7. What are the current fees and payment terms?
Module Learned Practised Mini-project
Basics and control [ ] [ ] [ ]
Functions [ ] [ ] [ ]
Data structures [ ] [ ] [ ]
OOP [ ] [ ] [ ]
Modules and pip [ ] [ ] [ ]
Error handling [ ] [ ] [ ]
Files, CSV, JSON [ ] [ ] [ ]
APIs with requests [ ] [ ] [ ]
Testing with pytest [ ] [ ] [ ]
Final project [ ] [ ] [ ]
1. Expense tracker (CLI): add, list and summarise expenses in a CSV
2. File organiser: sort files into folders by type and date
3. Weather or currency report: call a public API, save JSON, print summary
4. Quiz app: questions from JSON, scores saved to a file
Each project: functions, error handling, tests, README, Git history
SECTION 05Tips for getting the most from a Python course
These habits help beginners progress steadily:
- Code every day — even 30 minutes builds fluency.
- Read error messages — they usually tell you what went wrong.
- Build small projects early — apply each module right away.
- Use Git from the start — your history becomes your portfolio.
- Ask questions in class — small doubts grow if ignored.
SECTION 06Interview Q&A — Python beginners
Q1What is the difference between a list and a tuple?
A list is mutable and can be changed after creation; a tuple is immutable and is often used for fixed collections.
Q2What is a dictionary in Python?
A collection of key-value pairs with fast lookup by key, such as {'name': 'Asha', 'score': 92}.
Q3What does __init__ do in a class?
It initialises a new object, setting its starting attributes when the object is created.
Q4How do you handle exceptions in Python?
Use try and except to catch specific errors, optionally else and finally, and raise clear errors when input is invalid.
Q5What is a virtual environment?
An isolated Python environment for a project with its own installed packages, avoiding conflicts between projects.
SECTION 07Test yourself — Python beginners quiz
Five questions. No sign-up.
0 / 5Pick an answer to see why it is right or wrong.
SECTION 08Frequently asked questions
What does Uncodemy's Python programming course cover?
It typically covers Python basics, data structures, OOP, modules, error handling, files, APIs, libraries, testing and projects. Confirm the current official syllabus with a counsellor.
Is the Python course suitable for complete beginners?
Python courses usually start from the basics. Ask a counsellor about prerequisites and the pace of the batch.
How long is the Python programming course?
Duration and batch options can change. Talk to a counsellor for the current schedule.
What can I do after learning Python?
Python leads into data analytics, data science, web development with Django or Flask, automation and testing, depending on your interests.
What are the fees for the Python course?
Talk to a counsellor for current fees and payment options.
SECTION 09Related reads
Classroom & online · Noida
Explore the Python programming course
Our Python Training Course takes you from basics to OOP, files, APIs, testing and projects, with hands-on practice in every module.
Talk to a counsellor for current fees- Basics to OOP
- Files and APIs
- Testing and projects
- Weekday & weekend batches