A checklist is the list of requirements to complete this program and receive the award, as the college publishes it in its catalog. It is the same for everyone. It does not say what you have completed; that comes from applying your own record.
Program
- Award
- MS
- Credential class
- ceterms:MasterDegree
- CIP
- 30.7104
- Total credits (published)
- 31
- Credits (computed from items)
- 91
- Catalog edition
- 2025-2026
- Checklist type
- degree-program
Identifiers
- IPEDS UNITID
- 196413
- CourseShelf checklist
- CK_196413_f97bf3c6
- CollegeTransfer.Net
- Institution Transfer Profile
- Source
- CourseShelf publish 61
Requirements to complete
Every course or condition the catalog lists, in the catalog's order.
Program Requirements
0 items
Required Core
major core · 0 items
The 12-credit required core includes foundational knowledge in databases, data analysis and machine learning. Students will complete courses in an order which builds foundational knowledge and skills in preparation for more advanced work.
major core · 4 items
- 3
- 3
- 3
- 3
Electives
electives · 7 items
- Students can also choose any course from a different concentration for three credits, an additional course in the chosen concentration if available, or any course from the list below. Only 3 credits of IST 974 will count towards the 12 credits of required electives in the ADS program.Not resolved to a course12
- 3
- 3
- 3
- 1-3
- 3
- 3
Exit Requirement
0 items
Students take IST 782 in their last semester or term of study.
1 item
- 1
Concentration
concentration · 1 item
- Concentrations allow students to select course work that matches their professional interests and planned career paths. Students are required to select one concentration below, and complete two classes, or 6 credits, from that concentration.Not resolved to a course6
AI
0 items
Know how to use advanced deep learning predictive models in an ethical way
3 items
- 3
- 3
- 3
Big Data
0 items
Know how to use advanced applications, tools and packages to work with very large datasets
2 items
- 3
- 3
Data and Business Analytics
0 items
Understand how predictive analytics can be leveraged across a variety of business contexts to generate business insight.
6 items
- 3
- 3
- 3
- 3
- 3
- 3
Data Pipelines and Platforms
0 items
Improve your data engineering skills by practicing collecting data, parsing /munging the data, doing feature engineering as well as storing the data in an appropriate data repository.
3 items
- 3
- 3
- 3
Language Analytics
0 items
Understand how to work with unstructured textual data, via both text mining (looking for patterns in the words) and natural language processing (parsing and analyzing the text from a linguistics perspective)
2 items
- 3
- 3
Project Management
0 items
Know how to best manage and deliver useful, ethical, and actionable insight and tools.
2 items
- 3
- 3
Visual Analytics
0 items
Use visualization and interaction to generate insight from data and their associated predictive
2 items
- 3
- 3
Source. Syracuse University, catalog 2025-2026 — https://coursecatalog.syracuse.edu/graduate/information-studies/applied-data-science-ms/. Captured page pages/0574.html.gz. Assembled from the institution's published catalog as captured; every record names its captured page and source URL. Assembled, not asserted.