Big Data Analytics Adv. Cert.

Program Overview

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.

Graduate Admissions Counselor

Mandie Klingelhoffer

Department Contact

Hans-Peter Bischof, Ph.D.

Admission Deadlines & Requirements

Program Available Online? No
Application Deadline Rolling
Admit Term Fall/Spring/Summer
Entrance Exam
English Language Exams:
TOEFL (Internet)
PTE Academic


Priority deadline - COMPLETE applications that are received by this date are given priority consideration for admission and financial aid (if applicable). Applications received after the priority deadline will be considered on a space-available basis.

Rolling - There is no specific deadline for applications; applications will be accepted and reviewed throughout the year until the program reaches capacity.


Big data analytics, advanced certificate, typical course sequence

Course Cr. Hrs.
Required Courses
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-652    Distributed Systems  
   CSCI-654    Foundations of Parallel Computing  
   CSCI-721    Data Cleaning and Preparation  
   CSCI-729    Topics in Data Management  
   ISTE-724    Data Warehousing  
   ISTE-780    Data-driven Knowledge Discovery  
     Open Elective*  
Total Credit Hours 12

* Students who wish to take graduate elective courses not listed must obtain approval from their faculty adviser.

Admission Requirements

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.

Additional information

Study options

This certificate is intended for part-time study; therefore, RIT cannot issue I-20 paperwork.

Gainful employment

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

Career Outcomes

The RIT Office of Career Services and Cooperative Education website provides information pertaining to student skills and capabilities, salary data, career information, job outcomes, and contact information for the Career Services Coordinator by program.

Related Links

Program web site