Certificate of Advanced Study in Big Data Analytics
The 15-credit certificate program in Big Data Analytics is designed to address the needs of professionals with a Bachelor of Science or a Master of Science degree in Information Science or a related field in order to expand their professional skills and qualifications in effectively handling large amounts of disparate data.
Big data involves three major dimensions: data size, data rate, and data diversity. Students completing the certificate will gain essential, in-depth knowledge of techniques and technologies relevant for big data management.
The courses offered allow you to tailor your program of study to your individual interests.
Post-Bachelor’s students must complete three of the following courses with a grade of C or better; Post-Master’s students must complete three of the following courses with a grade of B or better:
- INFSCI 2160 Data Mining
- INFSCI 2591 Algorithm Design
- INFSCI 2711 Advanced Topics in Database Management
- INFSCI 2725 Data Analytics
Post-Bachelor’s students must complete two of the following courses with a grade of C or better; Post-Master’s students must complete two of the following courses with a grade of B or better:
- INFSCI 2130 Decision Analysis and Decision Support Systems
- INFSCI 2140 Information Storage and Retrieval
- INFSCI 2410 Introduction to Neural Networks
- INFSCI 2430 Social Computing
- INFSCI 2801 Geospatial Information Systems (GIS)
- INFSCI 2802 Mobile GIS and Location-Based Services
- INFSCI 2809 Advanced Geospatial Information Systems
- TELCOM 2125 Network Science and Analysis: Networks, Crowds, and Interconnected Worlds
- LIS 2690 Information Visualization
Requirements and Prerequisites
- Official transcript
- Two letters of recommendation that attest to the applicant’s aptitude and motivation to pursue studies at a level beyond the bachelor’s or master’s degree
- Personal statement
- Successful completion of at least one three-credit college course with a grade of B or better in each of the following:
- Structured programming language. A course on structured programming using Java, C# or C++ is required. Either INFSCI 0017 Object-Oriented Programming 1 for Information Science, CS 0401: Intermediate Programming Using Java is recommended to meet this requirement.
- Statistics. A course covering data collection, descriptive and inferential statistics is optimal. It should cover measures of central tendency and variability, regression, correlation, non-parametric analysis, probability and sampling, Bayesian analysis, significance tests, and hypothesis testing. Either STATS 0200: Basic Applied Statistics, or STATS 1000: Applied Statistical Methods is recommended to meet this requirement.
- Mathematics. A college-level mathematics course, in discrete mathematics or calculus, is required. Any of the following Pitt courses are recommended to meet the requirement: MATH 0120: Business Calculus, MATH 0220: Analytic Geometry and Calculus 1, or MATH 0400: Discrete Mathematical Structures.
15-Credit Post-Bachelor’s Certificates
A BS/BE degree from an accredited college or university in Computer Science, Information Technology, Telecommunications, Computer or Electrical Engineering, Mathematics or a related field with a scholastic average of a B (3.0 on a 4.0 scale) or better
15-Credit and 24-Credit Post-Master’s Certificates
A MS degree from an accredited college or university in Computer Science, Information Technology, Information Science, Telecommunications, Computer or Electrical Engineering, Mathematics or a related field with a scholastic average of a B (3.0 on a 4.0 scale) or better.
Tuition and Fees
Tuition rates and fees for the upcoming academic year can be found on the University’s Institutional Research Web site.