Feb 29, 2024  
2023-2024 Undergraduate Catalog 
2023-2024 Undergraduate Catalog

Data Intensive Computing Certificate

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Admission Criteria

Current students wishing to pursue the Data Intensive Computing Certificate, submit the School of Engineering and Applied Sciences Major/Minor Change Application. See the complete School of Engineering and Applied Sciences Admissions Policies for details.

Course Requirements

Additional Course Requirements (5 credits)

  • Any 300/400 level course with data intensive content in the major area of the student
  • Capstone project in the major area of the student 

Total Credits Required for Certificate: 23

Academic Requirements

Students must maintain a minimum of 2.500 GPA average in the required and elective courses in order to remain in the program and be awarded the certificate. The certificate is awarded concurrently upon completion of all program requirements and completion of a bachelor’s degree at the University at Buffalo. It cannot be awarded as a standalone certificate program even after the student has earned a bachelor’s degree.

Transfer Credit Policy

Equivalent transfer courses are acceptable for CSE 115   and CSE 116  . CSE 250  , CSE 486   and CSE 487  must be taken at UB.

Learning Outcomes

Upon successful completion of the certificate program students will have the ability to:

  • Recognize a data-intensive problem.
  • Assess the scale of data and requirements.
  • Retrieve data using appropriate methods.
  • Describe the data layout and define the data repository format (Ex: store).
  • Decide the algorithms (Ex: MapReduce) and programming models (Ex: Bayesian).
  • Define application-specific algorithms and analytics (Ex: network analysis).
  • Design the data-intensive program solution and system configuration.
  • Implement the data-intensive solution and test the solution.
  • Write a report summarizing the solution and results.
  • Incorporate services from cloud computing platforms.
  • Study the foundational concepts enabling cloud computing: services-based interface, programmatic consumption of services, virtualization, PKI-based security, large-scale storage, load-balancing, machine images and on-demand services.
  • Formulate data-intensive visualization solutions for presenting the results.


(HEGIS: 51.00 DATA PROCESS TECH UNCLAS, CIP11.0701 Computer Science)


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