Python Programming Course in Mumbai for Beginners

• Installing Python

  • the official installer
  • PATH problems on Windows
  • checking your version
  • python versus python3

• Running code

  • the interactive shell
  • running a script file
  • VS Code setup
  • reading a traceback

• Virtual environments

  • why global installs break
  • venv
  • activating and deactivating
  • requirements.txt

• Packages

  • pip install
  • finding a package on PyPI
  • pinning versions
  • what a dependency actually is

You can run Python from the terminal and manage a project environment.

• Variables

  • assignment and naming
  • dynamic typing
  • everything is an object
  • the id of an object

• Numbers

  • int and float
  • integer division and modulo
  • floating point surprises
  • round and decimal

• Booleans and None

  • truthy and falsy values
  • None versus False
  • is versus double equals

• Type conversion

  • int, float and str
  • when conversion raises
  • checking a type with isinstance

• Input and output

  • input returns a string
  • print with sep and end
  • f-strings
  • format specifiers inside f-strings

You can predict the type of any expression and convert between types safely.

• String basics

  • immutability
  • indexing
  • slicing
  • negative indices
  • len

• String methods

  • split and join
  • strip
  • replace
  • upper and lower
  • startswith and endswith
  • find

• Formatting

  • f-strings
  • alignment and padding
  • number formatting
  • multi-line strings

• Escape and encoding

  • escape sequences
  • raw strings
  • UTF-8 and why Indian language text breaks

• Regular expressions

  • the re module
  • matching patterns
  • groups
  • findall and sub
  • when a regex is the wrong answer

You can slice, search and reformat text without reaching for a loop.

• Conditionals

  • if, elif and else
  • comparison chaining
  • the conditional expression
  • match statements

• Loops

  • for over an iterable
  • while
  • range
  • enumerate
  • zip

• Loop control

  • break and continue
  • the else clause on a loop
  • nested loops

• Comprehensions

  • list comprehensions
  • conditions inside a comprehension
  • dict and set comprehensions
  • when a loop is clearer

• Iterables and generators

  • what makes something iterable
  • generator expressions
  • yield
  • lazy evaluation over a large file

You can express any loop idiomatically rather than translating from C.

• Lists

  • mutability
  • append, insert and pop
  • slicing and copying
  • sorting with key
  • the shallow copy trap

• Tuples

  • immutability
  • tuple unpacking
  • as dictionary keys
  • named tuples

• Dictionaries

  • key-value access
  • get with a default
  • iterating keys, values and items
  • dict ordering
  • nested dictionaries

• Sets

  • uniqueness
  • union, intersection and difference
  • membership testing cost
  • deduplicating a list

• Choosing a structure

  • lookup cost by structure
  • when a dict replaces a loop
  • collections Counter and defaultdict

You can pick the right structure and explain its lookup cost.

• Defining functions

  • parameters and arguments
  • return values
  • returning multiple values
  • docstrings

• Argument handling

  • default arguments
  • the mutable default trap
  • keyword arguments
  • args and kwargs

• Scope

  • local and global
  • the LEGB rule
  • closures
  • why global is usually wrong

• Functional tools

  • functions as objects
  • lambda
  • map and filter
  • sorted with a key function

• Modules and packages

  • import forms
  • writing your own module
  • the name equals main guard
  • package structure

You can write functions with clean signatures and organise them into modules.

• Classes and instances

  • defining a class
  • the init method
  • self
  • instance versus class attributes

• Methods

  • instance methods
  • class methods
  • static methods
  • properties and computed attributes

• Dunder methods

  • str and repr
  • len
  • eq and hash
  • making an object iterable

• Inheritance

  • subclassing
  • super
  • method overriding
  • multiple inheritance and the MRO

• Data classes

  • the dataclass decorator
  • default values
  • frozen instances
  • when a dataclass beats a dict

You can design a class with proper state and behaviour, and know when not to.

• File handling

  • open and the with statement
  • read modes
  • reading line by line
  • writing and appending
  • encoding

• Structured formats

  • the csv module
  • json load and dump
  • reading an Excel file
  • pathlib

• Exceptions

  • try, except and finally
  • catching specific exceptions
  • raise
  • custom exception classes
  • why bare except is dangerous

• Useful standard modules

  • datetime
  • os and sys
  • random
  • collections
  • itertools

• Logging

  • logging instead of print
  • levels
  • writing to a file
  • what to log in a script that runs unattended

You can read and write real file formats and handle failure deliberately.

• HTTP and APIs

  • the requests library
  • query parameters
  • status codes
  • parsing a JSON response
  • API keys and rate limits

• Web scraping

  • BeautifulSoup
  • finding elements
  • handling pagination
  • robots.txt and scraping responsibly

• Tabular data

  • pandas DataFrames
  • reading CSV and Excel
  • selecting and filtering
  • groupby
  • merging two tables

• Cleaning

  • missing values
  • type coercion
  • duplicates
  • normalising inconsistent text

• Databases

  • sqlite3
  • parameterised queries
  • writing a DataFrame to a table

You can pull data from a file, an API or a web page and reshape it.

• Command-line tools

  • argparse
  • exit codes
  • reading configuration from the environment
  • making a script runnable

• A web application

  • Flask routes
  • templates and Jinja
  • handling form input
  • connecting to a database
  • returning JSON

• Testing

  • pytest basics
  • writing a first test
  • testing a function with edge cases
  • why tests matter for a portfolio

• Version control

  • git init, add and commit
  • branches
  • pushing to GitHub
  • a README that explains the project

• Deploying

  • running on a free host
  • environment variables and secrets
  • what breaks in production that never breaks locally

You can build a small web application and put your work on GitHub.