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Graduate Students Converse in a Computer Lab

CPSC-51000 Introduction to Data Mining and Analytics

Credits: 
3
Prerequisites: 
(CPSC-50200 or MATH-51000) and (CPSC-50100, or CPSC-51100, or prior programming experience)

Overview of the field of data mining and analytics; large-scale file systems and Map-Reduce, measures of similarity, link analysis, frequent item sets, clustering, e-advertising as an application, recommendation systems.

Learning Objectives:

  1. Describe examples of the kinds of problems confronted by data scientists.
  2. Identify the technologies used by data scientists to manage and analyze large quantities of data.
  3. Explain how large-scale file systems are distributed across clusters of machines.
  4. Explain how Map-Reduce manages and queries data.
  5. Calculate measures of similarity, clusters, and frequency of item sets.
  6. Describe the components and function of recommendation systems.

YOUR OPPORTUNITY: You'll breathe life into the mathematics you've learned by pairing it with computing techniques that process and analyze large data sets.

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