Why choose Python?

Python has gained immense popularity and recognition around the world due to its readability, flexibility and versatility. Considered an easy-to-learn language, it is an excellent choice for people starting their programming adventure. It offers unlimited possibilities, covering areas from creating web applications to data analysis and artificial intelligence.

In recent years, Python has not only become the language of choice among developers, but has also gained popularity outside the traditional IT environment. This phenomenon was initially due to Python's dominance in the field of Data Analysis, and then its growing role in Machine Learning and Artificial Intelligence. This language is particularly appreciated as the first step in learning programming.

Additionally, Python is gaining more and more recognition in various industries, where it is becoming a language for automation and creating various scripts. For example, in engineering, more and more industry programs decide to use Python, which confirms its versatility and usefulness in everyday professional tasks. Therefore, by choosing Python, you open the gates to a full range of programming possibilities, meeting the needs of both beginners and experienced programmers in various fields of computer science.

What do we offer?

1. Fundamentals and advanced programming techniques: Master Python syntax from scratch and expand your skills by learning advanced programming techniques such as object-oriented programming, error handling, and frameworks.
2. Web Application Development with Django: Enter the world of web application development using the powerful Django framework. Learn to design effective, scalable and secure web applications.
3. Data Analysis and Machine Learning: Learn how to use Python to analyse data and build machine learning models. Hands-on training will enable you to apply algorithms to solve real-world problems.
4. Practice on projects: We don't just teach theory - our instructors guide you through practical projects, allowing you to apply your knowledge in real scenarios.

Our training not only teaches the syntax of this powerful language, but above all develops practical skills that are crucial for success in today's dynamic IT environment.

What makes our training unique?

• Experienced instructors: Our instructors are Python enthusiasts with extensive practical experience, ready to share their knowledge.
• Schedule flexibility: We offer a variety of schedules to suit your needs and learning pace.
• Certificate of completion: After completing the training, you will receive a certificate confirming the acquired knowledge and skills.

Open the door to an exciting programming career. Contact us to learn more about our Python programming training and start building your path to success in the world of coding!

10 tips for writing clean Python code:

1. Maintain PEP 8 compatibility: PEP 8 is the official style guide for Python. Follow it to maintain consistency in code formatting, indentation, variable names, and overall structure.
2. Apply the DRY (Don't Repeat Yourself) rules: Avoid repeating code. Instead, isolate repetitive fragments into functions, classes, or modules to make them easier to maintain and reduce the risk of errors.
3. Use descriptive names: Give your variables, functions, and classes names that describe their purpose. Avoid abbreviations and single-letter names unless they are commonly known (e.g. “and” in loops).
4. Use types and data typing: Take advantage of Python's dynamic scope, but also data typing, especially in functions and classes. This increases the readability of the code and makes it easier to understand the expected data.
5. Create short functions: Use the single responsibility principle. Functions should do one thing and do it well. Short functions are easier to understand, test, and maintain.
6. Avoid global variables: Limit the use of global variables because they can introduce unnecessary complexity and make debugging more difficult. If you must use a global variable, capitalize the name (convention).
7. Document your code: Use comments and docstrings to describe functions, classes, and code snippets. Well-documented code makes it easier to collaborate, understand, and maintain, even for other developers.
8. Test regularly: Implement unit tests and integration tests to ensure your code works as expected. Automated testing helps you avoid introducing errors when making changes.
9. Use Python lists and dictionaries: Take advantage of built-in data structures such as lists and dictionaries, rather than creating custom structures. This makes the code easier to understand and maintain.
10. Optimize for readability: Always follow the principle that code should be readable by other people. Avoid cleverly shortening your code too much, which can make it difficult to understand.