Data Mining Curriculum: A Proposal

Prerequisites

Data mining is a broad field that combines techniques from different areas in computer science and statistics. Our model curriculum assumes that students have basic background knowledge in the following areas:

Database Systems:
Data models, query languages, SQL, conceptual database design, query processing, and transaction processing.

Statistics:
Expectation, basic probability, distributions, hypothesis tests, ANOVA, and estimating a distribution parameter.

Linear Algebra:
Vectors and matrices, vector spaces, basis, matrix inversion, and solving linear equations.

Algorithms and Data Structures:
We assume familiarity with basic data structures and general maturity of students to understand algorithms written in pseudo-code.

We believe that most computer science seniors either have covered this material in previous courses, can pick up missing material in self-study, or that the missing material is introduced by the course instructor as necessary.

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