Advance Python Programming

Unlock your potential with our comprehensive Python Training course! Known for its simplicity and versatility, Python is a powerful language used in web development, data analysis, AI, and more. Through hands-on projects and real-world applications, you'll build a solid foundation and develop practical skills to tackle diverse challenges

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2 | 3 monthsCourse duration

Classroom | OnlineMode of Delivery

09Capstone projects

Why should you do this course?

Learn and grow as a developer with our project based courses.

Level up from Basic to Pro Coding Expert

Level up from Basic to Pro Coding Expert and master advanced Python concepts with ease. Enhance your problem-solving skills and stand out in today’s competitive tech industry sjksjks sjksjks sjkskjskj

Open doors to High-Paying Job Roles

Master both frontend and backend technologies and become a job-ready full stack developer, capable of handling entire application flows.

Automate Task and Optimize Workflow

MERN stack is one of the most popular stacks used by top companies. This course prepares you for full stack developer roles with strong job prospects.

Learn industry tools and best practices

Gain hands-on experience with Git, GitHub, REST APIs, JWT, MVC architecture, and deployment strategies used in real-world teams.

Our Scholarship test for Performance based fee waivers.

Starting from₹ 12000₹ 9000

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Key Highlights

Python programming courselearn Python onlinePython training for beginners

Live Projects

2 | 3 months duration

Certificate of Excellence/Completion

Placement assistance

Syllabus

Quickstart

Overview of the Journey

We offer live classes with expert instructors, weekly assignments to reinforce your learning, and fully practical training focused on real-world skills. You’ll work on hands-on projects throughout the course to build experience and confidence.

Datatypes and Variables

Datatypes

Data types are fundamental categories used to classify and represent different types of data, such as numbers, text, and more. Understanding Python data types is essential for effectively working with data and variables in your programs.

Variables

Variables are fundamental elements in Python and other programming languages that are used to store, manipulate, and manage data.

Conditional & Looping

Conditional Statement

In Python, the if statement is used for conditional execution, running a block of code when a condition is true. The else statement provides an alternative block if the condition is false. The elif statement (short for else if) lets you check multiple conditions in sequence, executing the code for the first true condition it encounters.

Looping Statement

Python uses conditional statements like if, elif, and else to control the flow of a program based on specific conditions. For repeating tasks, loops are used — the for loop iterates over a sequence, while the while loop continues as long as a condition remains true. You can also use nested loops, where one loop runs inside another, for handling complex, multi-level data structures. The break statement is used to exit a loop prematurely, and the continue statement skips the current iteration and moves to the next one.

Pattern Programming

Creative Pattern Programming in Python

Pattern programming in Python involves using loops, especially nested loops, to display specific sequences or shapes made of characters, numbers, or symbols. By controlling the number of iterations and applying conditions within loops, you can create patterns like triangles, pyramids, or number sequences. It’s a great way to practice looping, conditional statements, and nested structures, helping improve problem-solving and logic-building skills.

Special Datatypes

List & List Comprehensions

In Python, a list is a dynamic, ordered collection that can store multiple values of varying data types within a single variable. It supports a wide range of operations, including adding, removing, updating, and sorting elements. Complementing this, list comprehensions provide an elegant, concise syntax for generating new lists by embedding loops and conditional logic within a single, readable line. This approach enhances code efficiency and clarity, making it a powerful tool for data processing and transformation tasks.

Dictionary & Dictionary Comprehensions

Dictionary is an efficient, unordered collection that stores data as key-value pairs, allowing quick access and easy data management. Dictionary comprehensions offer a concise, elegant way to create or modify dictionaries using loops and conditions in a single line, making data processing faster and more readable.

Tuples, Sets & Boolean

A tuple in Python is an ordered, immutable collection used to store multiple values, ideal for fixed data sets. The boolean type represents logical values True and False, commonly used in decision-making and conditional operations. A set is an unordered collection of unique, immutable elements, perfect for tasks like removing duplicates or performing set operations such as union, intersection, and difference.

Functions & File Handling

Python Functions

Python functions enable modular, reusable code by encapsulating logic into named blocks. They can accept inputs, perform tasks, and use return statements to send results back to the caller. Recursion is a powerful technique where a function calls itself to solve problems iteratively, often simplifying complex tasks like traversing data structures or performing mathematical computations. Mastering functions, recursion, and return statements is key to writing clean, efficient, and elegant Python code.

Python File Handling

File handling in Python allows you to read, write, and manage files efficiently using built-in functions and context managers. Combined with the powerful os library, you can automate tasks like file organization, directory management, and system operations. Mastering these tools is essential for building automated workflows and handling persistent data in real-world applications.

Exception Handling

Ensure Robust and Reliable Applications

Python exception handling equips professionals with the tools to manage runtime errors proactively using structured try, except, else, and finally blocks. This approach ensures application stability and reliability by gracefully handling unexpected conditions, minimizing downtime, and enhancing user experience. Mastering exception handling is crucial for developing resilient, production-ready Python applications in dynamic business environments.

Decorators and Generators

Python Decorators

Python decorators are advanced programming tools that allow you to modify or extend the behavior of functions and classes without altering their code. By wrapping functions with additional logic, decorators help improve code modularity, maintainability, and reusability. They’re widely used in areas like logging, authentication, performance tracking, and access control in scalable, production-grade Python applications.

Python Generators

Python generators are a powerful tool for creating iterators in a memory-efficient way using the yield keyword. Unlike regular functions, generators produce values one at a time as needed, making them ideal for handling large data streams and optimizing performance in resource-intensive applications. Mastering generators enables professionals to build scalable, high-performance Python solutions for data processing, automation, and real-time systems.

Web Scraping & Data Collection

Web Data Collection and Scraping for Business Insights

Python web scraping is a practical technique for automatically extracting data from websites using libraries like BeautifulSoup and Requests. It enables professionals to collect, structure, and analyze web-based information for market research, competitive analysis, and data-driven decision-making. Mastering web scraping and data collection equips you to build automated data pipelines, streamline reporting, and support business intelligence in fast-paced, data-centric environments.

Object Oriented Programming

Build Scalable, Modular & Maintainable Applications with Python OOP

Python Object-Oriented Programming (OOP) is a powerful programming approach that organizes code into reusable, modular structures called classes and objects. It emphasizes core principles like encapsulation, inheritance, polymorphism, and abstraction, making code more maintainable, scalable, and efficient. OOP is widely used in developing complex applications, enterprise software, and automation solutions where clean architecture and code reusability are critical. Mastering Python’s OOP concepts equips professionals to design robust, flexible, and future-ready software systems.

Numpy & Pandas

Numerical Computing and Data Handling with NumPy

NumPy is a core Python library for efficient numerical computing and advanced data manipulation. It provides powerful support for multidimensional arrays, vectorized operations, and a wide range of mathematical functions. Widely used in data science, analytics, and machine learning, NumPy ensures fast, reliable performance for large-scale data processing.

Powerful Data Handling with Pandas

Pandas is a powerful, open-source Python library designed for efficient data manipulation, analysis, and preparation. It offers intuitive data structures like Series and DataFrames, enabling professionals to handle structured data with ease. Pandas simplifies complex tasks such as data cleaning, aggregation, transformation, and time-series analysis, making it an essential tool for data science, analytics, and business intelligence workflows.

Flask Web Framework

Simple and Flexible Web Development Using Flask

Flask is a lightweight, flexible Python web framework ideal for building scalable and maintainable applications. Its modular design offers developers full control and supports rapid development with a rich ecosystem of extensions. Mastering Flask enables efficient delivery of robust, customizable web solutions for modern business needs.

Why choose Datadrix?

Learn and grow as a developer with our project based courses.

Superb mentors

Best in class mentors from top Tech schools and Industry favorite Techies are here to teach you.

Industry-vetted curriculum

Best in class content, aligned to the Tech industry is delivered to you to ensure you Tech industry.

Project based learning

Hands on learning pedagogy with live projects to cover practical knowledge over theoretical one.

Superb placements

Result oriented courses across all genres, students as well as Working professionals.

Project based learning

Hands on learning pedagogy with live projects to cover practical knowledge over theoretical one.

Superb placements

Result oriented courses across all genres, students as well as Working professionals.

Certificate of completion

Joining DATADRIX means you'll create an amazing network, make new connections, and leverage diverse opportunities.

“Validate Your Expertise and Propel Your Career”

Expand Opportunities: Certifications to unlock new career opportunities, gain credibility with employers, and open doors to higher-level positions.
Continuous Growth: Certifications not only validate your current skills but also encourage continuous learning and professional development, allowing you to stay updated with the latest industry trends and advancements.
Certification: A testament to your skills and knowledge, certifications demonstrate your proficiency in specific areas of expertise, giving you a competitive edge in the job market.

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See what students have to say

Joining DATADRIX means you'll create an amazing network, make new connections, and leverage diverse opportunities.

Mayank Rana

Linked

I joined Datadrix to learn Python and Data Engineering. Thanks to Om Arora for simplifying coding concepts and providing practical projects to work on.