On this page: Data Science Track (Big Data • Mathematics and Data • Natural Language Processing) • Data Science Biomedical Informatics (Medical School) Track • Biomedicine Research • Biomedicine Electives)
The CDS Master’s in Data Science (MSDS) offers two primary “tracks” of study:
- The Data Science track
- The Data Science – Biomedical Informatics (Medical School) track
Within the Data Science track, students can specify an area of interest, such as Big Data, Mathematics and Data, or Natural Language Processing. These tracks are designed to help students focus their elective coursework and assist CDS in understanding demand for different course offerings during admissions. Students may change tracks until the end of their second semester.
Data Science Track
In the Data Science track, students take six required courses and six elective courses from a diverse list of offerings.
Areas of Interest within the Data Science Track:
Big Data
Electives that fall within this area of interest include:
- DS-GA 1012: Natural Language Understanding and Computational Semantics
- DS-GA / CSCI-GA 2433: Database Systems
- CS-GY 6083 Principles of Database Systems
- CS-GY 6093: Advanced Database Systems
- CS-GY 6313: Information Visualization
- CS-GY 6323: Large-Scale Visual Analytics
- CSCI-GA 2434: Advanced Database Systems
- CSCI-GA 2436: Realtime and Big Data Analytics
- CSCI-GA 2437: Big Data Application Development
- CSCI-GA 3033: Cloud and Machine Learning
- CSCI-GA 3033: Introduction to Deep Learning Systems
- INTG1-GC 1025: Database Management & Modeling
- MATH-GA 2047: Trends in Financial Data Science
- TECH-GB 2350: Robo Advisors & Systematic Trading
Mathematics and Data
Electives that fall within this area of interest include:
- DS-GA 1013: Mathematical Tools for Data Science
- DS-GA 1005: Inference and Representation
- CSCI-GA 2945/MATH-GA 2012: Convex and Nonsmooth Optimization
- CSCI-GA 3033/DS-GA 3001: Special Topics: Mathematics of Deep Learning
Natural Language Processing
Electives that fall within this area of interest include:
- DS-GA 1005: Inference and Representation
- DS-GA 1008/CSCI-GA 2572: Deep Learning
- DS-GA 1011: Natural Language Processing with Representation Learning
- DS-GA 1012: Natural Language Understanding and Computational Semantics
- DS-GA 1015: Text as Data
- CSCI-GA 2590: Natural Language Processing
- CSCI-GA 3033: Learning with Large Language and Vision Models
- CSCI-GA 3033: Statistical NLP
Data Science Biomedical Informatics (Medical School) Track
The Data Science – Biomedical Informatics (Medical School) track is designed for students interested in the rapidly growing field of biomedical informatics, which has influenced many recent healthcare developments, including new opportunities for personalized medicine. These innovations, along with the recent growth in high-throughput genomics technologies, have created a high demand for skilled biomedical informatics professionals.
The capstone project for this track will be biomedicine-based and completed with a biomedicine mentor. In addition to the 6 required courses, students pursuing this track take a selection of the following courses in both Biomedicine Research and Biomedicine Electives:
Biomedicine Research
Select 2 of the following:
- BMIN-GA 0003: Advanced Topics in Biomedical Informatics (formerly Introduction to Biomedicine)
- BMIN-GA 1003: Introduction to Health Informatics
- BMIN-GA 3001: Topics in Bioinformatics
Biomedicine Electives
Select 2 of the following:
- BMIN-GA 4498: Advanced Integrative Omics
- BMIN-GA 3002: Clinical Decision Support Systems
- BMIN-GA 3007: Deep Learning for Biomedical Data
- BMIN-GA 3008: Evaluation Methods in Health IT
- BMIN-GA 4500: Approaches in Microbiome Research
- BMIN-GA 3004: Next Generation Sequencing
- BMIN-GA 3003: Proteomics Informatics