Graduate Certificate in Applied Data Science

Graduate Certificate in Applied Data Science

Description

This certificate is designed to provide hands-on training in the area of applied data science.  Coursework focuses on developing knowledge and skills in critical reasoning, measurement development, evaluation, data management, data analytic software utilization, multivariate data analysis and modeling, data visualization, machine learning, data mining, cloud computing, and big data techniques.

The Applied Data Science (ADS) Certificate program is offered online through the Engineering Graduate Programs office in the College of Engineering & Science.

Open All | Close All

  •  

    Program Learning Outcomes

    Upon completion of the Applied Data Science Graduate Certificate, graduates will be able to:

    1. apply data science concepts and methods to solve problems in real-world contexts;
    2. demonstrate competencies in data mining and machine learning techniques, including classification, clustering, feature extraction, visualization, and dimensionality reduction;
    3. use statistical software packages to apply a variety of statistical techniques to diverse data types and structures;
    4. demonstrate an understanding of the strengths, limitations and assumptions of specific statistical methods;
    5. develop the ability to build and assess data-based and machine learning models as well as an understanding of model implementation in real-world settings.
  •  

    Certificate Requirements (15 credits)

    This is a 15-credit (five-course) certificate program. Nine credits (three courses) are required core courses, and six credits (two courses) are electives, which may be chosen from the list below.

    Students must maintain a minimum 3.0 GPA in both the certificate program and overall. Grades below "C" will not advance a student towards graduation.

    CSSE 5110 is a co-requisite or prerequisite for all other requirements, so should be taken first.

    Required Courses (9 credit hours)

    • CSSE 5110 Quantitative Foundations for Data Analysis (3 credits)
    • CSSE 5120 Introduction to Data Science (3 credits)
    • CSSE 5310 Data Mining (3 credits)

    Elective courses (choose two courses - six credit hours)

Program Contact Information

Shadi Bani Taan, Ph.D.
Director Computer Science/Software Engineering
Email: banitash@udmercy.edu
Telephone: 313-993-1060

Paul Spadafora
Director of Professional Engineering Programs & Industry Liaison
Email: spadafpa@udmercy.edu
Telephone 313-993-1603

Valarie Steppes-Glisson, Administrative Assistant
Professional Engineering Programs Office - Engineering 202
Telephone: 313-993-1128
Fax: 313-993-1955
Email: glissovs@udmercy.edu

 

For more information:  Applied Data Science website