Big data is noted for its volume, varieties of data types, and rapid accumulation. Big data has become a catchphrase to describe data collections that are so large they are not amenable to processing or analysis using traditional database and software techniques. The advanced certificate in big data analytics is a multidisciplinary program intended for professionals with BS degrees in computing or other diverse fields such as finance, retail, science, engineering, or manufacturing—areas where knowledge of how to analyze big data is necessary. The advanced certificate is also meant for students who would like a formal qualification in this area. The program allows professionals with a bachelor's degree to enhance their career opportunities and professional knowledge with targeted graduate course work in a focused area without making a commitment to an MS program.
Plan of study
The goal of the program is to develop expertise in managing and analyzing big data. The program consists of two required courses and two elective courses selected by the student in topic areas related to big data.
Big data analytics, advanced certificate, typical course sequence
|CSCI-620||Introduction to Big Data||3|
|CSCI-720||Big Data Analytics||3|
|Electives*–Choose two of the following:||6|
|CSCI-621||Database System Implementation|
|CSCI-622||Secure Data Management|
|CSCI-654||Foundations of Parallel Computing|
|CSCI-721||Data Cleaning and Preparation|
|CSCI-729||Topics in Data Management|
|ISTE-780||Data-driven Knowledge Discovery|
|Total Credit Hours||12|
* Students who wish to take graduate elective courses not listed above must obtain approval from their faculty adviser.
To be considered for admission to the advanced certificate in big data analytics, candidates must fulfill the following requirements:
- Complete a graduate application.
- Hold a baccalaureate degree (or equivalent) from an accredited university or college in science, computing, engineering, or a related major.
- Applicants with undergraduate degrees from foreign colleges and universities are required to submit GRE scores. GRE scores from other students may be requested.
- Submit a personal statement of educational objectives outlining the applicant’s research/project interests, career goals, and suitability to the program.
- Submit two letters of recommendation from academic or professional sources.
- Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
- Have a minimum cumulative GPA of 3.0 (or equivalent)
- Have acceptable college level credit or practical experience in probability and statistics, computer programming in a high-level language, and database systems.
This certificate is intended for part-time study; therefore, RIT cannot issue I-20 paperwork.
Information regarding costs and the U.S. Department of Labor’s Standard Occupational Classification (SOC) code and occupational profiles for this program can be viewed at www.rit.edu/emcs/financialaid/gedt/2017-2018/big-data-analytics.html.