The graduate certificate in Database and Data Mining is a Purdue University degree offered in the Department of Computer and Information Sciences.
Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables. Findings are then validated by applying the detected patterns to new subsets of data. The ultimate goal of data mining is prediction. Predictive data mining is the most common type of data mining and one that has the most direct business applications.
This certificate introduces students to the core concepts necessary for the design, implementation, and application of database systems. It stresses the fundamental principles in database modeling and design. The aim is to address the continuing need for engineering databases for complex and ever changing applications requiring security, performance, and reliability. Here’s what you’ll learn in the certificate program:
- the logical design of database systems
- the entity-relationship model
- semantic model
- hierarchical model
- network model implementations of the models
- design theory for relational database
- design of query languages and the use of semantics for query optimization
- design and verification of integrity assertions and security
- introduction to intelligent query processing and database machines
Students must complete 12 graduate credit hours. After finishing the requirements for the graduate certificate, you may opt to finish the remaining requirements toward the M.S. degree, although admission is not guaranteed.
Understanding the requirements
One core course
- CSCI 50300 (Operating Systems) or 58000 (Algorithms)
Three specialization courses
- CSCI 54100 (Databases)
- CSCI 57300 (Data Mining)
- CSCI 59000 (Distributed Databases)