About this courseSkip About this course
This course will also cover related methods for discovering structure in unlabeled data, such as factor analysis and clustering. It will also cover related methods for relationship mining including how to validly conduct correlation mining and how to automatically discover association rules and sequential rules.
This mini-course does not assume prior programming knowledge beyond what you will already have learned in other courses in this MicroMasters, although advanced tools will be discussed for interested students.
This course includes content also offered in the University of Pennsylvania’s edX MOOC, Big Data and Education, weeks 4, 5, and 7.
What you'll learnSkip What you'll learn
- Domain structure discovery (how to map content to skills/concepts)
- Knowledge inference (calculating what a student knows)
- Cluster and Factor Analysis
- Correlation Mining
- Association and Sequential Pattern Mining
Week 2: Knowledge Inference: Bayesian Knowledge Tracing, Performance Factors Analysis, Item Response Theory, and Deep Learning
Week 3: Relationship Mining: Correlation Mining, Association Rule Mining, and Sequential Pattern Mining
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