Description
Object-Oriented Programming in Python course. Learn how to use Python for detailed data analysis with our course on object-oriented programming (OOP). This course, “Understanding OOP in Python: Learning about classes, inheritance, polymorphism, and improving code for advanced data analysis and machine learning,” will give you an in-depth understanding of OOP. This helps you write code that is easy to update and can handle large amounts of data. Start with the basics of how to design a class and explore the details of inheritance and polymorphism. These are important tools for writing robust and reusable code. You will learn how to find problems in your code, and how to improve your code to make it better and faster. This is a vital skill for any coder. We look at real-world examples of machine learning to help you understand how OOP works in practice. This will be very useful for your own data projects. This course also has a special section with advanced ChatGPT commands. These are designed to make you think, help you remember what you’ve learned, and provide a place to explore tough questions about OOP. This course prepares you to learn more complex data processing and machine learning techniques using Python. It’s a great resource for data scientists and students who want to get better at coding. So immerse yourself in this complete OOP course and unlock new opportunities in your journey with data analysis.
What you will learn in the Object-Oriented Programming in Python course
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Master Python’s OOP principles: Unleash the power of classes, methods, and objects to design robust, scalable software.
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Unravel the mystery of inheritance and polymorphism: Learn how to reuse and extend code to create efficient and versatile applications.
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Enhance your code with refactoring: Learn techniques to transform your code into clean, efficient, and readable scripts.
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Learn to apply OOP concepts in real-world contexts: look at applications such as machine learning.
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Smell the code smells: Gain expertise in identifying and solving common coding problems to maintain high-quality code.
This course is suitable for those who
- Python students: Those who have completed the basics of Python and want to improve their skills by learning object-oriented programming.
- Data scientists and machine learning engineers: Professionals who want to use OOP principles to write more efficient and manageable machine learning code.
- Software Engineers: Those who want to improve their Python code structure, scalability, and maintainability by adopting OOP principles.
- Students and Educators: People in academia who want to enhance their understanding of Python and OOP for teaching, learning, or research purposes.
- Anyone interested in Python OOP: This course is suitable for those who are curious about object-oriented programming and want to further explore Python’s capabilities.
Description of the Object-Oriented Programming in Python course
- Publisher: Udemy
- Lecturer: Renato Boehmer
- Training level: Beginner to advanced
- Training duration: 0 hours and 56 minutes
- Number of courses: 11
Course Topics Object-Oriented Programming in Python
Object-Oriented Programming in Python Course Prerequisites
- Python Fundamentals: Basic understanding of Python data types, control flow, loops, and functions.
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