Object-Oriented Programming in Python

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Renato Boemer

41:24

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1 - Introduction

1 - Introduction.mp4

05:34

2 - ObjectOriented Programming Basics

2 - OOP Basics.mp4

04:33

2 - Pandas API Reference.txt

2 - Pandas Official Documentation.txt

2 - Python Builtin Functions.txt

2 - Python Official Documentation.txt

3 - Defining a Class.mp4

05:31

4 - Creating and Using Objects.mp4

04:30

5 - What is self in a Python class.html

3 - Inheritance

6 - Basics of Inheritance.mp4

08:49

7 - Inheritance vs Composition.html

4 - Polymorphism

8 - Basics of Polymorphism.mp4

06:52

5 - Decorators

1 - Decorator Quiz.html

9 - Using Decorators.mp4

05:35

6 - Advanced OOP with ChatGPT

10 - Prompts that will take you to the next level.html

7 - EXTRA Refactoring Your Code

11 - Introduction to Refactoring.html

Description

Mastering Class Design, Inheritance, Polymorphism, and Code Refactoring for Efficient Data Analysis and Machine Learning

What You'll Learn?

Master Python's OOP Fundamentals: Unleash the power of classes, methods, and objects to design robust, scalable software.
Demystify Inheritance & Polymorphism: Understand how to reuse and extend code to create efficient, versatile programs.
Elevate Your Code with Refactoring: Learn techniques to transform your code into clean, efficient, and readable scripts.
Understand How to Apply OOP Concepts in Real-World Contexts: Look into practical applications like machine learning.
Sniff Out Code Smells: Gain expertise in identifying and resolving common coding pitfalls to maintain high-quality code.

Who is this for?

Python Students: Those who have been through the basics of Python and want to advance their skills by learning about object-oriented programming.

Data Scientists and Machine Learning Engineers: Professionals who are looking to leverage OOP principles to write more efficient and manageable machine learning code.

Software Engineers: Those aiming to improve their Python code structure, scalability, and maintainability by adopting OOP principles.

Students and Educators: Individuals 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 anyone curious about object-oriented programming and looking to delve deeper into Python's capabilities.

What You Need to Know?

Python Fundamentals: a basic understanding of Python data types, control flow, loops, and functions.

More details

Description
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 & Machine Learning," gives you a deep understanding of OOP. This will help you write code that's easy to update and can handle a lot of data.
Start with the basics of how to design a class and discover the details of inheritance and polymorphism. These are important tools for writing strong, reusable code. You'll learn to spot problems in your code, and how to improve your code to make it better and faster. This is a key skill for any coder.
We'll look at real-world examples from machine learning to help you understand how OOP works in practice. This will be really useful for your own data projects. The course also has a special section with advanced ChatGPT prompts. These are designed to make you think, help you remember what you've learned, and provide a space to explore difficult questions about OOP.
This course will set you up to learn more complex data processing and machine learning techniques using Python. It's a great resource for data professionals and students who want to get better at coding. So dive into this complete OOP course and open up new opportunities in your journey with data analysis.
Who this course is for:
Python Students: Those who have been through the basics of Python and want to advance their skills by learning about object-oriented programming.
Data Scientists and Machine Learning Engineers: Professionals who are looking to leverage OOP principles to write more efficient and manageable machine learning code.
Software Engineers: Those aiming to improve their Python code structure, scalability, and maintainability by adopting OOP principles.
Students and Educators: Individuals 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 anyone curious about object-oriented programming and looking to delve deeper into Python's capabilities.

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Hi there! I'm Renato, a Machine Learning and Math specialist with a keen interest in teaching and mentoring. Currently, I'm proudly associated with Le Wagon, Europe's leading Data Science bootcamp where I share my passion and knowledge with budding data professionals.Previously, I had the opportunity to work as a Data Scientist for a US-based social media company where I applied my skills to solve complex business challenges. My academic journey took me to the University of Cambridge, where I delved deep into Neuroscience, further cultivating my love for intricate patterns, statistics and data.I believe in the power of education and am driven by the desire to make high-quality, industry-relevant courses accessible to all. Specifically, I'm focused on helping students who aspire to apply Machine Learning and Python in STEM fields. My courses are designed with an understanding of student needs and industry trends, balancing theory and practice, and always prioritizing clarity and engagement.Join me as we unravel the complexities of Machine Learning and Python together!

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