Indiana University Purdue University Indianapolis

Graduate Certificate in Databases and Data Mining

The program will introduce 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. The program emphasizes fundamentals for:

  • 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 will be able to ...

  • List and explain the fundamental concepts of a relational database system.
  • Utilize a wide range of features available in a DBMS package.
  • Analyze database requirements and determine the entities involved in the system and their relationship to one another.
  • Develop the logical design of the database using data modeling concepts such as entity-relationship diagrams.
  • Create a relational database using a relational database package.
  • Manipulate a database using SQL.
  • Assess the quality and ease of use of data modeling and diagramming tools.

Program Requirements

A graduate certificate will be issued when a student has completed 12 graduate credit hours in one of the specialization areas. After finishing the requirements for the graduate certificate, the student may opt to finish the remaining requirements towards a MS degree.*

  • 1 Core Course: CSCI 503 (Operating Systems) or 580 (Algorithms)
  • 3 Specialization Courses:
    • 54100 (Databases)
    • 57300 (Data Mining)
    • 59000 (Distributed Databases)

What is Data Mining?

Data Mining is an analytic process designed to explore data (usually large amounts of data - typically business or market related) in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data. The ultimate goal of data mining is prediction - and predictive data mining is the most common type of data mining and one that has the most direct business applications. The process of data mining consists of three stages:

  • the initial exploration
  • model building or pattern identification with validation/verification
  • deployment (i.e., the application of the model to new data in order to generate predictions)

Student Consumer Information About this Program

*Admission and completion of Certificate does not guarantee MS program admission.

 


If you have any questions regarding the Computer & Information Science  Graduate Program please contact admissions@cs.iupui.edu.