Big and Smart Data Sciences Graduate Certificate (BASM-CERTD)

Program Description

There is an unprecedented growth in data collected by all types of organizations for various scientific, medical, financial, and other purposes. This is a result of activities in an interconnected world. These activities include our social activities on the web by using sensors and other high throughput devices on or around individuals and around the globe. This has given rise to Big Data, characterized by 5Vs (volume, velocity, variety, veracity and value). Smart Data is about intelligent processing of Big Data for improved insights and decision-making for enterprises and individuals. Data sciences is about creative approach, methodologies, and techniques that span data acquisition to analysis and applications. This unique certificate in Big and Smart Data Sciences will equip a student in pursuing a highly sought after data scientist’s career in managing Big Data and helping create Smart Data-enabled applications for enterprises and individuals.

Admissions Requirements

Students must meet the modified M.S. admissions requirements as follows:

B.S. degree in computer science, computer engineering, or information sciences
Minimum GPA 3.0
Minimum combined GRE 298

Exceptions

A student with a B.S. degree in science or engineering will be conditionally admitted to the certificate program with the requirement to complete the core courses (CS-5100 Data Structures and Algorithms, and CEG-6350 OS Internals and Design).
GRE requirement is waived for an applicant, if the applicant:
- Is a Wright State ECS graduate with minimum GPA 3.3; or
- Has a graduate degree in science or engineering from a U.S. institution of higher education; or
- Has three or more years of work experience in software development/analysis; or
- Is a non-degree graduate student who has accumulated 9 or more hours of CS/CEG graduate courses and has minimum GPA 3.3

For More Information

Program Requirements:

Select 6 Courses from the Following

CEG 6520 - Scientific Visualization Credit Hour(s): 3
CEG 7380 - Cloud Computing Credit Hour(s): 3
CS 6370 - Parallel Programming for Many-Core GPUs Credit Hour(s): 3
CS 7700 - Advanced Database Systems Credit Hour(s): 3
CS 7800 - Information Retrieval Credit Hour(s): 3
CS 7720 - Advanced Data Mining Credit Hour(s): 3
CS 7810 - Metadata Representation Languages Credit Hour(s): 3
CS 7820 - Advanced Topics in Semantic Web Credit Hour(s): 3
CS 7830 - Machine Learning Credit Hour(s): 3
CS 7900 - Special Topics in Computer Science Credit Hour(s): 1 to 4
CEG 6970 - Independent Study in Computer Engineering Credit Hour(s): 1 to 6 with Special permission of the graduate director
OR
CS 6970 - Independent Study in Computer Science Credit Hour(s): 1 to 6 with Special permission of the graduate director
CEG 7920 - Independent Study in Computer Engineering Credit Hour(s): 1 to 6 with Special permission of the graduate director
OR
CS 7920 - Independent Study in Computer Science Credit Hour(s): 1 to 6 with Special permission of the graduate director

Total: 18 Hours

Note(s): If the MS student is doing a thesis that is in the areas covered by this certificate, the student may petition reduction in formal course work for 3 to 6 credits.