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Certificate of Graduate Study

Topological Data Analysis

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Deliver Insights through the Structure of Data


Online Program

Become proficient in the contemporary applications and methodologies that fuel modern artificial intelligence. With this unique training program, you will acquire a mathematical background and learn new topological data analysis techniques to extract valuable information from large volumes of multi-dimensional data.

From linear algebra and persistent homology to Morse theory and the Mapper algorithm, the certificate program in topological data analysis (TDA) will equip you for advanced positions in areas including technology, actuarial science, insurance, finance, state government and biomedical research.

Program of Study

programofstudy

The program starts with a background in linear algebra, graph theory and homological algebra. After this preparation, you will learn about persistent homology, the first major tool in TDA. This includes the basics of discrete Morse theory necessary for implementations of persistent homology in the “big data” setting. The last major topic in the program is the Mapper algorithm. The Mapper is applied to feature selection and feature generation in machine learning and to the architecture of artificial neural nets for deep learning.
 

Required Courses (9 credits)

  • Linear Algebra for Applications
  • Topological Data Analysis I 
  • Topological Data Analysis II

You can complete this certificate program as a standalone credential, or you can gain the equivalence of 9 elective credits toward the master's program in data science.

As this is a part-time fully asynchronous online program, you will have the flexibility to access course materials, discussion forums and assignments during times that fit your schedule.


Additional Information

See the Graduate Bulletin for details.

For more information, contact the Data Science Team at [email protected]​​​​​​​.

Career Outcomes

This program prepares you for the growing needs of academia and industry to manage big data sets using the most contemporary mathematical tools.
In addition, the topological data analysis program provides an excellent foundation for further graduate studies in areas including computer science, biology, psychology, geography, atmospheric science, chemistry and sociology.


Potential job titles include:

  • Data Analyst 
  • Data Engineer 
  • Data Research Analyst

 

 

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careers

International Students

This degree is designated as a STEM program. International students maintaining F-1 status are allowed to apply for up to 12 months of post-completion Optional Practical Training (OPT) following completion/graduation from their degree program. Currently, this degree program is also designated by the Department of Homeland Security (DHS) as an eligible degree for the F-1 STEM OPT work authorization extension; students who secure qualifying employment may be eligible to apply for the STEM OPT extension for a cumulative total of up to 36 months of F-1 OPT work authorization.

Admissions Requirements
Deadlines
  • Fall: Rolling
  • Spring: Rolling
  • Summer: Rolling

There is no departmental assistantship consideration for this program.

Required Application Materials
  • Transcripts from all schools attended
  • Statement of goals

The statement is generally one to two pages discussing what you have to offer the program and what you wish to get out of the program.  It should include a brief description of the applicant's field of interest, related background, desired area of study and research emphasis or career goals. 

Special Notes

Please Note: This program is not eligible for federal financial aid

admissions
Student Learning Objectives


Learning objectives that UAlbany students are expected to attain through their course of study within their academic program.

CGS
  • Understand the fundamental principles of Topological Data Analysis (TDA) at the level common among PhD graduates in the field
  • Ability to critically choose the framework and appropriate software implementation of the TDA methods used in a specific project
  • Gain essential experience in a variety of settings where TDA has become a go-to tool in modern data science workflows
  • Have expertise in TDA methods available for use in artificial intelligence projects that use machine learning and statistical analysis
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