Overview
Curriculum
In this module, we will cover the essentials of machine learning using Python. We will explore key concepts like supervised and unsupervised learning, model selection, and training, along with popular libraries like scikit-learn. We’ll work through the process of preparing data, selecting the right algorithms, evaluating model performance, and applying machine learning techniques to real-world problems. By the end of this module, you’ll have a strong foundation in applying machine learning methods and be equipped to take on machine learning projects with confidence.
What You'll Learn
- Explain core OOP concepts and how they help structure ML code
- Describe the machine learning process and key terminology
- Understand how scikit-learn’s estimator API works
- Choose models and tune hyperparameters using scikit-learn
- Use supervised learning to predict customer churn with real-world data
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