Python is a versatile, high-level programming language that is easy to interpret, interactive, and object-oriented. It is widely used for software development and is open-source. The Python course doesn't have difficult prerequisites, but students are expected to be patient, attentive, and have some basic programming knowledge. Analytical skills are also important for those aiming to become successful programmers.

If you're looking to build your skills, enrolling in an online & offline Python course is an excellent option. But where should you begin? What does the Python course cover? How long does it take, and what are the costs involved?

This guide will answer all these questions and provide details on the Python course syllabus for 2025.

What is Python Programming?

Python is a well-known and flexible programming language used in many areas such as web development, data analysis, scientific research, automation, and more.

Its easy-to-understand syntax and simplicity make it highly recommended for beginners, making it a great starting point for those new to programming.

Uses of Python

What is a Python Course?

A Python course is an organized program that teaches people how to use the Python programming language.

These courses are designed for learners at all levels, from complete beginners to experienced programmers who want to enhance their skills.

Python Course in Mumbai - Key Highlights

1. Python Introduction and Setting up the Environment

The first part of the course introduces learners to Python programming, including how to download and set up the environment, as well as Python IDEs. You'll also learn where Python is commonly used and why it's becoming popular in Data Science.

Topics covered in this section:

• Introduction to Programming

• Python vs. R

• Why Python is ideal for Data Science

• Python-related job roles

• Different Python IDEs

• Downloading and setting up the Python environment

2. Python Basic Syntax and Data Types

After installing Python, the next step is learning how to write a program. This part of the course covers basic syntax, input/output operations, comments, variables, data types, and typecasting in Python. You’ll learn how to store data in different types and how to change data from one type to another.

Topics covered in this section:

• Input and output operations in Python

• Comments in Python

• Variables and naming rules

• Basic Data Types

• Typecasting in Python

3. Operators in Python

Operators tell the computer to perform specific tasks on variables and values. Python has different types of operators, each with its own function. For example, the "+" operator is used for addition. In this part of the course, you’ll learn about each type of operator, when to use them, and how they work.

Topics covered in this section:

• Arithmetic operators

• Assignment operators

• Comparison operators

• Logical operators

• Identity operators

• Membership operators

• Bitwise operators

4. Strings in Python

Strings are sequences of letters, words, or characters and are important for data manipulation. This section of the course introduces you to strings, how they are represented, various string methods, as well as string indexing, slicing, and formatting.

Topics covered in this section:

• Creating strings

• String formatting

• Indexing

• Slicing

• String methods

5. Lists

Lists are used by Python programmers to store multiple items in a single variable. They are one of Python's main data types, identified by square brackets. List items maintain an order, can be changed, and allow duplicate values. This part of the course explains how to create lists, use indexing and slicing, and introduces list methods.

Topics covered in this section:

• Creating lists

• Properties of lists

• List indexing

• List slicing

• List of lists

• List methods

• Adding, updating, and removing elements from lists

6. Tuples

Tuples are another in-built data type in Python that can store multiple items in a single variable. Unlike lists, tuples are written within round brackets and cannot be changed once created. This section provides detailed information on tuples, including their syntax, properties, and methods.

Topics covered in this section:

• Syntax for creating tuples

• Tuple properties

• Indexing tuples

• Slicing tuples

• Tuple methods

7. Sets

Sets are a key part of Python’s in-built data types, used to store multiple items in a single variable. Unlike lists and tuples, sets are written within curly brackets and are unordered, unchangeable, and unindexed. In this section, you’ll learn about sets, how they differ from lists and tuples, and how to use set operations and methods.

Topics covered in this section:

• Syntax for creating sets

• Updating sets

• Set operations and methods

• Differences between sets, lists, and tuples

8. Dictionaries

Dictionaries are one of the four main data types in Python, used to store data in key-value pairs. They are written within curly brackets. This section covers how to create dictionaries, store data, and access elements using keys and values, along with various dictionary methods.

Topics covered in this section:

• Syntax for creating dictionaries

• Storing data in dictionaries

• Keys and values in dictionaries

• Accessing elements in dictionaries

• Dictionary methods

9. Python Conditional Statements

When writing Python programs, you often need to use conditions. For instance, if a condition is true, one statement is executed; otherwise, a different one runs. This section explains how to use Python's conditional statements like "if," "if-else," and "if-elif-else" to set logic in your code.

Topics covered in this section:

• Setting logic with conditional statements

• If statements

• If-else statements

• If-elif-else statements

10. Loops in Python

Loops are essential for executing statements repeatedly until a condition is met. Python primarily uses "while" and "for" loops. This section covers how to use these loops, along with the "break," "continue," and "pass" statements, and the "range" function.

Topics covered in this section:

• Iterating with loops

• While loop

• For loop

• Range function

• Break statement

• Continue statement

• Pass statement

• Enumerate

• Zip

• Assert

11. List and Dictionary Comprehension

List and dictionary comprehension provide a concise way to create new lists or dictionaries based on existing ones. This section explains why and how to use list and dictionary comprehensions.

Topics covered in this section:

• Purpose of list comprehension

• Syntax for list comprehension

• Syntax for dictionary comprehension

12. Functions

Functions are blocks of code that run only when called and return results. This section covers how to create and use functions, handle arguments, and understand global and local variables, as well as recursion.

Topics covered in this section:

• What functions are

• Modularity and code reusability

• Creating functions

• Calling functions

• Passing arguments

• Positional arguments

• Keyword arguments

• Variable-length arguments (*args)

• Variable keyword-length arguments (**kwargs)

• Return keyword

• Passing functions as arguments

• Returning functions

• Global and local variables

• Recursion

13. Anonymous Functions

Anonymous functions, or lambda functions, are functions without names and can be used immediately or stored in a variable. They can accept any number of arguments but have only one expression. This section covers how to use lambda functions.

Topics covered in this section:

• Lambda functions

• Lambda with filter

• Lambda with map

• Lambda with reduce

14. Generators

Generators are functions that act like iterators and are a shortcut for creating iterators. This section will teach you how to create and use generators.

Topics covered in this section:

Creating and using generators

15. Modules

Modules are like code libraries in Python, containing definitions and statements that can be imported into other modules or the main program. This section covers how to create modules, import functions and variables from them, and use Python's built-in modules.

Topics covered in this section:

• Creating modules

• Importing functions from other modules

• Importing variables from other modules

• Python built-in modules

16. Packages – Data Analysis

Data analysis involves examining, cleaning, transforming, and modeling data to extract useful information and aid decision-making. This section teaches how to use Python packages such as NumPy, Pandas, and Matplotlib for data analysis, including creating packages and importing modules from them.

Topics covered in this section:

• Creating packages

• Importing modules from packages

• Different ways to import modules and packages

• Working with NumPy, Pandas, and Matplotlib

17. Exceptions and Error Handling

When a Python program encounters an error, it usually stops and displays an error message. This section explains how to handle errors and exceptions to keep your program running smoothly using try, except, and finally blocks, as well as addressing syntax and logical errors.

Topics covered in this section:

• Syntax errors

• Logical errors

• Handling errors using try, except, and finally

18. Classes and Objects (OOP)

Python is an object-oriented programming language, which means that everything is treated as an object. This section introduces you to classes and objects, which are essential concepts in Python. You will learn about creating classes and objects, understanding attributes and methods, inheritance, polymorphism, and operator overloading.

Topics covered in this section:

• Creating classes and objects

• Attributes and methods

• Using the init constructor method

• Class and instance attributes

• Different types of methods (instance, class, static)

• Inheritance (single, multiple, multilevel)

• Overriding parent methods

• Using the super() function

• Polymorphism

• Operator overloading

19. Date and Time

The datetime module in Python helps manage and work with date and time. This section covers how to use the datetime, date, and time modules, including operations like formatting and parsing dates and times.

Topics covered in this section:

• date module

• time module

• datetime module

• Time delta

• Formatting date and time

• Using strftime()

• Using strptime()

20. Regex

Regular Expressions (Regex) are a powerful tool for matching patterns in text. This section explains how to use the re module in Python to work with regular expressions, including common functions and meta characters.

Topics covered in this section:

• Using regex

• re.search()

• re.compile()

• re.findall()

• re.split()

• re.sub()

• Meta characters and their usage

21. Files

Files are used to store data in Python, and this section teaches you how to handle files, including opening, reading, writing, and closing them.

Topics covered in this section:

• Opening files

• Handling different file types

• Reading, writing, and closing files

• Using different file modes

22. Web Scraping

Web scraping involves extracting data from websites, which is especially useful for data analysis. This section introduces you to web scraping using BeautifulSoup and techniques for scraping both static and dynamic websites.

Topics covered in this section:

• Installing BeautifulSoup

• Understanding web structures

• Using Chrome DevTools

• Using requests

• Scraping data from static websites

• Scraping dynamic websites

23. Database Access

Python can be used to interact with databases. This section covers the basics of working with MySQL, including creating tables, inserting values, and querying databases.

Topics covered in this section:

• Accessing databases using MySQL

• Creating tables

• Inserting values

• Committing changes

• Querying, updating, and deleting data

24. Working on Data Analysis

Data analysis involves collecting, transforming, and organizing data to make informed decisions. In Python, you can use libraries like NumPy and Pandas for this purpose. This section covers how to perform data analysis and visualization.

Topics covered in this section:

• Introduction to NumPy and working with multidimensional arrays

• Exploring data with Pandas (Exploratory Data Analysis - EDA)

• Data visualization techniques

25. APIs: The Unsung Hero of the Connected World

APIs (Application Programming Interfaces) allow you to retrieve data from various sources. This section introduces you to APIs and demonstrates how to access public APIs for tasks such as retrieving weather data.

Topics covered in this section:

• Introduction to APIs

• Accessing and using public APIs

26. Python for Web Development – Flask

Flask is a lightweight Python framework for building web applications. This section guides you through installing Flask and using it to develop web applications.

Topics covered in this section:

• Introduction to Flask

• Installing Flask

• Handling different HTTP methods (GET, POST, PUT)

• Working with templates and the render_template function

Python Full Stack Developer Course Syllabus 2025

A Python Full Stack Developer course in Mumbai includes a broad range of topics, focusing on both front-end and back-end development. Students will learn to use Python along with other related technologies to build complete applications, including:

Front-End Development:

• HTML, CSS, and JavaScript basics.

• Responsive design and CSS frameworks like Bootstrap.

• Advanced JavaScript and frameworks like React or Angular.

Back-End Development with Python:

• Python server-side programming with Flask or Django.

• Handling HTTP requests/responses and setting up the development environment.

Databases and Data Management:

• Working with relational databases (e.g., MySQL, PostgreSQL) and ORMs like SQLAlchemy. Data validation and security practices.

Authentication and Authorization:

• User authentication, session management, and implementing OAuth or JWT.

RESTful API Development:

• Building and testing APIs with Python frameworks, and API design principles.

Deployment and Hosting:

• Deploying applications to servers, containerization with Docker, and cloud platforms.

Version Control and Collaboration:

• Using Git and GitHub/GitLab for version control and collaborative development.

Testing and Debugging:

• Writing and running unit/integration tests, debugging techniques, and CI/CD.

Security:

• Web application security practices and handling vulnerabilities.

Performance Optimization:

• Identifying bottlenecks, caching strategies, and scaling.

Real-Time Applications:

• WebSockets and building real-time features.

Final Project:

• Designing and building a full-stack application with presentation and demonstration.

Career Development:

• Resume building, job search strategies, and interview preparation.

Python Course Admission Procedure

You don't need any specific exams or qualifications to enroll in a Python course in Mumbai. After finishing your 12th grade, you can apply to institutes that offer Python language courses.

You can choose to apply for either an Python online or offline certification course in Mumbai. To get started, visit the DeveLearn institute's official website to fill out the admission form with the required details. Once you've registered, the institute will contact you to provide further instructions.

Python Course Duration and Fees 2025

The length and fees of Python course in Mumbai can vary widely based on factors such as course level, the offering institution or platform, and location.

Here is a basic overview of possible durations and fees ranges for Python courses in Mumbai:

Enroll for Python Course in Mumbai

Python Course Eligibility 2025

Python courses are generally accessible to learners with various backgrounds and levels of experience. Eligibility can vary based on the course type, institution, or platform. Here are some general guidelines:

Growing Demand for Python Skills

The demand for Python skills remains strong and continues to rise across various industries and job roles. Several factors contribute to this growing need:

Python Job Profiles and Career Paths 2025

Python is used in a variety of job roles across different industries. Here are some common job profiles that involve Python:

Python Course Salary in 2025

Salaries for Python-related jobs in India vary based on experience, location, and industry. Here are the estimated salary ranges for Python roles in 2025:

Python Course in Mumbai

Python certification courses are among the most sought-after credentials in the tech industry. At DeveLearn, known as one of the best Python training institutes in Mumbai, you can enroll in online or offline Python courses that offer top-notch training and job placement assistance. If you're looking for Python training in Mumbai with placement support, DeveLearn provides the resources and support needed to help you succeed in the competitive job market. A Python certification from DeveLearn can open doors to high-paying job opportunities.