Course Content
Python for Data Analysis
Learn the Python fundamentals necessary for working with data and preparing datasets for analysis.
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Data Cleaning & Visualization
Learn how to prepare messy datasets and create visualizations that communicate meaningful insights.
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Introduction to Machine Learning
Understand how machines learn from data and build your first predictive models.
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Data Science Foundations

Machine learning approaches fall into two major categories.

Supervised Learning

Uses labeled data — the correct answer is provided during training.

Examples:

  • House price prediction
  • Spam detection

Unsupervised Learning

Uses unlabeled data — the model discovers structure on its own.

Examples:

  • Customer segmentation
  • Clustering similar articles

Understanding the difference is critical when selecting the right modeling approach for a given problem.