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As the size and availability of datasets increase, so too do the challenges in efficiently and effectively sharing, analyzing, and visualizing information. Proficiency in big data analytics requires knowledge in interdisciplinary areas including computer science, business information technology, mathematics and statistics, and electrical and computer engineering. This is a specialized graduate certificate program to teach practicing computing professionals and graduate students the skills that are necessary for the use and development of big data management, big data analytics, data mining, cloud computing, and business intelligence.
The graduate certificate program is open to all individuals holding a BS degree in computer science, engineering, or a scientific discipline, and who have a minimum of two years of professional experience, or are currently accepted into a graduate degree program at Missouri S&T. The only additional requirement for students entering a graduate certificate program is that they satisfy the prerequisites for any course they take in the program.
The certificate program consists of four courses: two are core courses and two are elective courses. In order to receive a Graduate Certificate, the student must have an average graduate cumulative grade point average of 3.0 or better in the certificate courses taken.
Students admitted to the certificate program will have non-degree graduate status, but will earn graduate credit for the courses they complete. If the four course sequence approved by the graduate advisor is completed with a grade of B or better in each of the courses taken, the student will upon application be admitted to the MS program in computer science as long as they have a BS in computer science, electrical engineering, or computer engineering, and as long as they meet the minimum undergraduate GPA requirements and core computer science course requirements. All computer science certificate courses and up to one non-computer science certificate course taken by the students admitted to the program will count towards their computer science MS degree.
Once admitted to the program, a student will be given three years to complete the program as long as a B average is maintained in the courses taken.
- COMP SCI 5402: Data Mining & Machine Learning
- COMP SCI 6304: Cloud Computing and Big Data Management
Choose one of the following five courses:
- IST 5420: Business Analytics and Data Science
- COMP ENG 6330 / ELEC ENG 6340 / SYS ENG 6214 /COMP SCI 6405/STAT 6239: Clustering Algorithms
- ERP 5410: Use of Business Intelligence
- COMP SCI 6301: Web Data Management and XML
- COMP SCI 6302: Heterogeneous and Mobile Databases
Choose one of the following four courses:
- COMP SCI 5300: Database Systems
- IST 6444: Essentials of Data Warehouses
- COMP SCI 6402: Advanced Topics in Data Mining
- STAT 5814: Applied Time Series Analysis
*There is overlap between the course offerings for this graduate certificate and other graduate certificates. No course can be used to satisfy the requirements for more than one certificate.
Course description can be found in the catalog at catalog.mst.edu/graduate.
Graduate certificates were designed as a gateway to a master’s degree. If a student earns a B or better in each certificate course they may continue for the graduate degree (in the corresponding department), without needing to submit GRE/GMAT scores, or letters of recommendation. A student does not need to continue on for the graduate degree, however most do. Graduate certificates were designed for working professionals who have real life work experience and may not have time to take the GRE/GMAT. Admission requirements for the graduate certificate program are also more relaxed than the graduate degree. This graduate certificate may act as a gateway to the following master’s programs:
Computer Science (MS)