Python Machine Learning Course Using Jupyter Lab

This introductory Python machine learning course using Jupyter Lab is designed to give you a quick, practical entry into the world of machine learning. No prior programming experience is required! Through engaging content and hands-on labs, we will guide you from an absolute beginner to someone equipped with fundamental machine learning skills using Python and Jupyter Lab.

This course is entirely practical and hands-on, focusing on building and evaluating prediction models using simplified, pre-cleaned datasets.

Skills you will acquire include:

• Get a strong foundation in Python 3, including essential programming concepts.
• Learn to create and manage Jupyter Notebooks within Jupyter Lab.
• Perform data analysis and visualizations to uncover insights using Python libraries.
• Understand and implement linear regression for predictive modeling.
• Utilize the scikit-learn library for various machine learning tasks and model building.
• Assess your machine learning models using metrics like MAE, MSE, RMSE, and R2Score.
• Create and customize visualizations to better understand your data.
• Validate your machine learning models using the train-test split method.
• Discover additional learning materials and datasets for further studies in machine learning.

This introductory Python machine learning course is perfect for anyone wanting a quick, hands-on introduction to machine learning, complete beginners in machine learning, and those who want to learn how to create Jupyter Notebooks using Jupyter Lab instead of Anaconda. Enroll today and get a taste of machine learning, equipping yourself with the skills to tackle more advanced topics in the future. Start your journey with us, and see you inside!