2019-2020 Graduate Course Catalog 
    Sep 29, 2022  
2019-2020 Graduate Course Catalog [ARCHIVED CATALOG]

Data Science, CAS

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Murali Venkatesh
Program Director
210 Hinds Hall
(315) 443-2911



The Certificate of Advanced Study (CAS) in Data Science program requires 15 credit hours and prepares students to work with large amounts of data using information technologies as tools to gain knowledge and insight. The 2 Core Courses (6 credits) focus on handling data through its full lifecycle: architecting, acquiring, analyzing, and archiving data. The remaining elective credits enable specializations in data analytics, data storage and management or other areas such as data visualization.

The certificate can be completed as a full-time or part-time student. All candidates should have a bachelor’s degree or equivalent. In addition, it is recommended that potential students have a strong background in science, statistics, research, and/or information technology. Applicants should have an interest in interdisciplinary work focused on managing big data using information technologies as tools. Prospective students who have an interest in data science, but lack the recommended undergraduate background, are encouraged to inquire. Individual consultations are available for such prospective students to explore their potential candidacy. We also offer our CAS in Data Science online. Learn more about iSchool@Syracuse Online.

Student Learning Outcomes

1. Document, analyze, and translate needs into technical designs and informatics solutions

2. Explain the general data lifecycle and relevant techniques from data acquisition, transformation, storage, retrieval, analysis, visualization, preservation, and publishing/sharing

3.  Apply various mathematical concepts, algorithms, technical standards, and principles to small and big data sets

4. Develop and deliver professional communications in the field.   Liaise with a range of people, including business managers, scientists, and IT developers

5. Apply privacy and ethics principles in data management and analysis

6. Employ data storytelling and dive into the data, find useful patterns, and articulate what patterns have been found, how they are found, and why they are valuable and trustworthy


This certificate requires 15 graduate credits. All courses are 3 graduate credits unless specified otherwise.

I. Required Courses (6 credits)

II. Elective Courses (9 credits)

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