Take your Python skills to the next level. This advanced course is designed for developers ready to move beyond the basics and explore Python’s more powerful features. With a strong focus on real-world application, you’ll master advanced topics such as object-oriented programming, testing, debugging, multithreading, database integration, and network communication. Whether you're working in data analysis, geo-information, or software development, this course will equip you to write efficient, scalable, and maintainable Python code.
Python Advanced
PythonPython
Introduction to Python Programming
Python is one of the most widely used programming languages in the world—and for good reason. Its clear syntax and unmatched versatility make it a top choice for beginners and experienced developers alike. From web development and automation to artificial intelligence, scientific research, and geo-information systems, Python plays a critical role in almost every area of tech.
Its interpreter-based model allows you to write and run code quickly, making it perfect for rapid prototyping and fast development cycles—especially in high-speed industries like geospatial analysis and data science. Libraries like NumPy, SciPy, Pandas, and GeoPandas provide Python with advanced capabilities to work with large, complex datasets, whether structured, time-based, or location-driven.
But to unlock Python’s full potential in professional settings, a deeper skill set is essential. Writing high-quality code that is clean, reliable, and adaptable requires more than just basic syntax knowledge. Advanced programming techniques—like error handling, modular design, database interaction, and parallel processing—are key to building robust, production-level software. That’s exactly what this course helps you master.
To get the most out of the Advanced Python Course, we highly recommend completing our Basic Python Course first—it lays the essential groundwork you’ll build on throughout the program.
What will you learn
In the Advanced Python Programming Course, you’ll strengthen your foundational knowledge and push further into the capabilities that set expert developers apart. You’ll start by diving deep into object-oriented programming (OOP), learning how to design reusable, maintainable code using classes, inheritance, polymorphism, and design patterns.
You’ll also focus on writing cleaner, more efficient code using modular structures and best practices for code formatting and structure. The course introduces tools to help you handle real-world challenges, like exceptions, logging, and debugging. You’ll also build and run unit tests, making your software more stable and dependable.
As you progress, you’ll explore advanced functions like lambdas, decorators, and generators, giving you new ways to write compact, high-performance code. You’ll connect Python to popular databases like SQLite and PostgreSQL, learning how to run SQL queries within your scripts and manage large datasets with ease.
In the final part of the course, you’ll tackle concurrency and process communication. You’ll learn how to use sockets, pipes, threading, and multiprocessing to create responsive programs that perform multiple tasks at once. You’ll also work with Anaconda and Jupyter Notebooks to manage your environment and keep your projects organized—especially helpful when working with complex data or presenting your work interactively.
Why choose this course
If you already know the basics and want to become truly fluent in Python, this course is your next step. Here’s why developers choose this program:
- Expert-led and industry-relevant: Taught by professionals with hands-on experience in Python and geo-information development.
- Practical, hands-on learning: Real-world projects and exercises ensure you’re not just learning concepts—you’re applying them.
- Tailored to data and geo-information needs: Learn how to work with structured and spatial data, which is essential in today’s job market.
Course structure
Day 1
The course kicks off with a review of core programming concepts like collections and functions, then dives into object-oriented programming. You’ll learn how to build reusable and structured code using classes, instances, and inheritance. Later, you’ll explore more advanced OOP techniques like polymorphism and design patterns. Throughout the day, you’ll work on hands-on exercises to reinforce your understanding and apply what you’ve learned to real-world problems.
Day 2
You’ll begin the day with structured approaches to error handling that make your code more stable. Then, you’ll explore Python’s logging features and debugging tools to identify and fix problems efficiently. The session wraps up with unit testing, giving you the ability to create automated tests that catch bugs before they impact your application.
Day 3
On day three, the focus shifts to writing efficient code. You’ll work with Lambda functions, recursion, decorators, and generators to improve memory management and performance. Later in the day, you’ll learn how to connect Python to databases like SQLite and PostgreSQL, and how to run SQL queries from within your scripts. You’ll practice loading, managing, and analyzing data—skills that are essential in any data-driven role.
Day 4
The final day introduces you to organizing your code using modules and packages. You’ll also learn how to prepare your applications for distribution. Then, the focus turns to parallel programming. You’ll explore sockets and pipes for process communication, and learn how to use threading and multiprocessing to build programs that can handle multiple tasks simultaneously. These skills are key for creating fast, responsive, and efficient software.
Learning Outcomes
- Design and maintain complex Python applications using object-oriented programming principles
- Apply advanced techniques including exception handling, logging, debugging, and unit testing
- Write efficient, modular Python code using functions, decorators, and generators
- Connect to and query databases using SQLite and PostgreSQL through Python
- Use argparse and syntax highlighting to build clear, user-friendly command-line tools
- Set up and manage robust development environments with Anaconda and Jupyter Notebooks
- Understand and apply multithreading, multiprocessing, and process communication
- Choose and work with different Python interpreters such as CPython, Jython, and IronPython based on project requirements
More Information?
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
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Frequently Asked Questions About Python Advanced
This course provides advanced knowledge in Python, with a focus on testing, debugging, packaging, multithreading, databases and network sockets.
This course is ideal for experienced Python programmers who want to deepen their knowledge and expand their skills.
Important packages such as NumPy, SciPy and Pandas are covered, essential for advanced data analysis.
The course lasts 4 days and is intensive and practice-oriented.
Yes, the course contains hands-on exercises and practical examples to apply the theory.
Basic Python skills are required, such as knowledge of basic syntax and simple data structures.
Yes, after the course there is the opportunity to ask questions to the teacher via email.
Yes, it is possible to take the course online via Google Meet.
Yes, discounts are available: 10% for 3 students and 15% from 4 students.
You can enroll directly via the registration widget (right side of desktop and mobile at the top).