| DIT 54110 | 48 |
This course introduces the fundamentals of machine learning theory and algorithm design that is necessary to adapt and apply AI to solve real-world problems. The course provides a foundational understanding of various machine learning and statistical pattern recognition algorithms and, using available machine learning platforms, teaches practical and applied design, testing, and implementation of learning models.
Prerequisites
Each course fee is paid for at the time of registration.
Outcomes
- Describe and apply AI learning algorithms and models, including rule and tree-based classifiers, uncertainty modeling, clustering and correlation techniques, and numeric prediction.
- Design, construct, test, and implement learning using AI tools/platforms and supporting programming languages.
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