CDS offers the Industry Concentration for the MS in Data Science. This concentration is specifically targeted to respond to the needs and inputs from companies and allows MS in Data Science students to apply the knowledge and skills obtained in their coursework to industry during the degree program. It requires more industry-targeted coursework and a Practical Training experience. This concentration has a required internship within the first year of study. International students should consult NYU’s Office of Global Services on how to obtain early CPT status within their first year if in this concentration.
Students in this concentration will be required to take the following courses for the degree as a part of the 36 credit requirement:
- DS-GA 1009 Practical Training for Data Science within the first year of the program (3 credits in fall, spring, or summer)
- 2 electives within the Big Data or Natural Language Processing subject areas (6 credits, see below for more details).
The courses below fall within the Big Data subject area. This list is approved and reviewed annually by the curriculum committee.
- DS-GA 1012: Natural Language Understanding and Computational Semantics
- CS-GY 6313: Information Visualization
- CS-GY 6323 Large-Scale Visual Analytics
- CS-GY 6083 Principles of Database Systems (Engineering School)
- DS-GA / CSCI-GA 2433 Database Systems (Courant Computer Science)
- CS-GY 6093: Advanced Database Systems (Engineering School)
- CSCI-GA 2434 Advanced Database Systems (Courant Computer Science)
The courses below fall within the Natural Language Processing subject area. This list is approved and reviewed annually by the curriculum committee.
- DS-GA 1011 Natural Language Processing with Representation Learning
- DS-GA 1012 Natural Language Understanding and Computational Semantics
- CSCI-GA 3033 Statistical NLP
- DS-GA 1005 Inference and Representation
- DS-GA 1008 / CSCI-GA 2572 Deep Learning
- DS-GA 1015 Text as Data
- CSCI-GA 2590 Natural Language Processing
All other requirements remain the same. See the MS Curriculum page for more information on the MS in Data Science curriculum.