Big and Smart Data Sciences Certificate

Program Description:

There is an unprecedented growth in data collected by all types of organizations, for various scientific, medical, financial, and other purposes, as a result of activities in interconnected world including our social activities on the Web, by using sensors and other high throughput devices on or around individuals and around the globe, and so on. 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 Computer Science & Engineering 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 MS Admissions requirements as follows:

A B.S. degree in Computer Science or 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
1. is a Wright State ECS graduate with minimum GPA 3.3, or
2. has a graduate degree in science or engineering from a U.S. institution of higher education, or
3. is a non-degree graduate student who has accumulated 9 or more hours of CS/CEG graduate courses and has minimum GPA 3.3, or
4. has 3 or more years work experience in software development/analysis.

For additional information:

Program Requirements:

Select 6 Courses from the Following

CEG 7380 - Cloud Computing Credit Hour(s): 3
CS 7700 - Advanced Database Systems Credit Hour(s): 3
CS 7900 - Special Topics in Computer Science Credit Hour(s): 1 to 4
CS 7810 - Metadata Representation Languages Credit Hour(s): 3
CS 7820 - Advanced Topics in Semantic Web Credit Hour(s): 3
CS 7740 - Diverse Data Analytics Credit Hour(s): 3
CS 7800 - Information Retrieval Credit Hour(s): 3
CS 7830 - Machine Learning Credit Hour(s): 3
CS 7720 - Advanced Data Mining Credit Hour(s): 3
CEG 6520 - Scientific Visualization Credit Hour(s): 3
CS 7920 - Independent Study in Computer Science Credit Hour(s): 1 to 6 or
CEG 7920 - Independent Study in Computer Engineering Credit Hour(s): 1 to 6

Total: 18 Hours

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
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
OR
CS 7920 - Independent Study in Computer Science Credit Hour(s): 1 to 6
With Special permission of the graduate director

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.