The DSAN Master’s program in Data Science and Analytics offers various concentration tracks to allow students to specialize in specific areas. The various concentration tracks are summarized below.
Artificial Intelligence (A.I.)
Focuses on developing algorithms that can learn from data to make predictions.
Required electives (in recommended chronological order):
- DSAN 6600: Neural Networks and Deep Learning
- DSAN 6650: Reinforcement Learning
- DSAN 6500: (Computer vision) or DSAN 6850: (NPL w/ LLM)
- DSAN 6725: Applied Generative AI for AI Developers
Remaining electives (select-two):
- DSAN 5400: Computational Linguistics – Advanced Python
- DSAN 6100: Optimization
- DSAN 6400: Network Analytics
- DSAN 5600: Applied Time Series for Data Science
- DSAN 5800: Advanced Natural Language Processing
- DSAN 6550: Adaptive Measurement with AI
- DSAN 7000: Advanced Research Methodologies (Capstone Project)
Natural Language Processing (NLP)
Specializes in the analysis and processing of human language data. Key topics include text mining, speech recognition, deep learning, machine translation, and sentiment analysis, and LLMs.
Required electives (in recommended chronological order):
- DSAN 5400: Computational Linguistics – Advanced Python
- DSAN 6600: Neural Networks and Deep Learning
- DSAN 5800: Advanced Natural Language Processing
- DSAN 6850: NLP with Large Language Models
Remaining electives (select-one):
- DSAN 5600: Applied Time Series for Data Science
- DSAN 6100: Optimization
- DSAN 6650: Reinforcement Learning
- DSAN 7000: Advanced Research Methodologies (Capstone Project)
Data Visualization and Communication
Emphasizes the creation and presentation of visual representations of data. It includes courses on data storytelling, information design, and advanced visualization techniques.
Required electives:
- DSAN 5900: Digital Storytelling
- DSAN 6750: Geographic Information Systems (GIS) and Applications
- DSAN 5450 (Ethics) or DSAN 6700 (ML-App deployment) (or both)
Remaining electives (select-two):
- DSAN 5600: Applied Time Series for Data Science
- DSAN 6300: Database Systems and SQL
- DSAN 5700: Blockchain Technologies for Data Science
- DSAN 6800: Principles of Cybersecurity
- DSAN 5500: Data Structures, Objects, and Algorithms in Python
Financial
Data Science plays a pivotal role in the finance industry, with opportunities to work in areas like banking and as financial analyst at other tech companies. This track prepares you to analyze complex financial data, helping organizations make informed decisions and optimize their performance. Whether you’re interested in becoming a financial analyst, a bank data specialist, or a risk manager, this track provides the expertise needed to succeed in the financial sector.
Required electives:
- DSAN 5600: Applied Time Series for Data Science
- DSAN 6600: Neural Networks and Deep Learning
- DSAN 5700: Blockchain Technologies for Data Science
- DSAN 6800: Principles of Cybersecurity
Remaining electives (select-two):
- DSAN 5450 (Ethics) or DSAN 6700 (ML-App deployment)
- DSAN 5900: Digital Storytelling
- DSAN 6300: Database Systems and SQL
- DSAN 6850: NLP with Large Language Models
Generalist
Students do not have to choose a specific concentration track. If no track is selected, students are free to “mix and match” electives to best suit their academic interests. Such a track would give students a general exposure to the field of data science and analytics, covering data collection, analysis, visualization, machine learning, NLP and big data technologies.
Possible Example:
- Fall-1 Elective:
- DSAN 6300: Database Systems and SQL
- Spring-1 Elective:
- DSAN 5500: Data Structures, Objects, and Algorithms in Python or
- DSAN 5400: Computational Linguistics – Advanced Python
- Fall-2 Electives:
- DSAN 6600: Neural Networks and Deep Learning
- DSAN 6700: Machine Learning App Deployment
- Spring-2 Elective:
- DSAN 5900: Digital Storytelling
NOTE: If you prefer to learn NLP in depth, please take DSAN 5800: Advanced Natural Language Processing which will be offered in Fall.