The scikit-learn team introduces a MOOC to allow aspirants to learn about the machine learning library, scikit-learn. Currently, the free course is available on a website created by Jupyter Notebook. However, the full-fledged course will be hosted on Fun MOOC in the coming months.
Any enthusiast can take this course as it is devised for learners of all categories. But, there are a few prerequisites like Python programming, NumPy, Pandas, and Matplotlib. According to the scikit-learn team, the goal of this course is to teach machine learning with scikit-learn to beginners, even without a strong technical background.
Being one of the most widely used machine learning libraries among machine learning practitioners for predictive modeling, scikit-learn is a crucial library to learn.
The course has a wide range of topics covered with a few quizzes to allow learns to gain a complete understanding of predictive machine learning. With modules like hyperparameter tuning, linear models, decision tree models, ensemble models, and more, it makes an ideal course to learn from and master the most in-demand skills.
Aspirants will also learn to create machine learning pipelines, select the best models, feature selection, evaluate model performance, and interpret features of models, making it a good mix of skills to gain for machine learning aspirants.