11  Concentration Tracks

12 Proposal: Concentration tracks

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.

13 Course schedule

Students can choose from a 1.5 or 2 year course of study, centered around the following core-classes.

Spring graduation (2 years)

Fall-1:

  • DSAN 5000: Data Science and Analytics

  • DSAN 5100: Probabilistic Modeling and Statistical Computing

  • Elective-1

Spring-1:

  • DSAN 5200: Advanced Data Visualization

  • DSAN 5300: Statistical Learning

  • Elective-2

Fall-2:

  • DSAN 6000: Big Data and Cloud Computing

  • Elective-3

  • Elective-4

Spring-2: (graduate)

  • Elective-5

  • Internship (Optional)

Fall graduation (1.5 years): Replace Elective-5 from the Spring-2 semester with a Summer elective .

Fall Target Audience
DSAN 5400: Computational Linguistics – Advanced Python both
DSAN 5550: Data Science and Climate Change both (but ideally 2nd)
DSAN 5800: Advanced Natural Language Processing second year
DSAN 6150: Biological and Biomedical Data Science both
DSAN 6300: Database Systems and SQL both
DSAN 6600: Neural Networks and Deep Learning both
DSAN 6650: Reinforcement Learning second year
DSAN 6700: Machine Learning App Deployment second year
DSAN 6750: Geographic Information Systems (GIS) and Applications both
DSAN 7000: Advanced Research Methodologies (Capstone Project) second year


Summer Target Audience
DSAN 6400: Network Analytics both
DSAN 6500: Image Mining and Computer Vision Analytics both


Spring Target Audience
DSAN 5400: Computational Linguistics – Advanced Python both
DSAN 5450: Data Ethics and Policy both
DSAN 5500: Data Structures, Objects, and Algorithms in Python both
DSAN 5600: Applied Time Series for Data Science both (but ideally 2nd)
DSAN 5700: Blockchain Technologies for Data Science both
DSAN 5900: Digital Storytelling both
DSAN 6100: Optimization both
DSAN 6550: Adaptive Measurement with AI second year
DSAN 6600: Neural Networks and Deep Learning both
DSAN 6800: Principles of Cybersecurity both
DSAN 6850: NLP with Large Language Models (LLMs) second year

14 Concentration tracks

Note: Students can request for minor course substitutions within concentration tracks from the Program Director. These requests maybe granted if the recommended substitution is a suitable match for the relevant concentration.

14.1 Generalist track

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.

14.2 Deep learning track:

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)

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 7000: Advanced Research Methodologies (Capstone Project)

Example-1:

  • Fall-1 Elective: DSAN 6600: Neural Networks and Deep Learning

  • Spring-1 Elective: DSAN 5600: Applied Time Series for Data Science

  • Fall-2 Electives:

    • DSAN 6650: Reinforcement Learning

    • DSAN 5800: Advanced Natural Language Processing

  • Spring-2 Elective: DSAN 6850: NLP with Large Language Models

Example-2:

  • Fall-1 Elective: DSAN 6600: Neural Networks and Deep Learning

  • Spring-1 Elective: DSAN 5600: Applied Time Series for Data Science

  • Summer Elective: DSAN 6500: Image Mining and Computer Vision Analytics

  • Fall-2 Electives:

    • DSAN 6650: Reinforcement Learning

    • DSAN 5800: Advanced Natural Language Processing

14.3 Natural language processing(NLP) track:

  • 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)

Example:

  • Fall-1 Elective: DSAN 5400: Computational Linguistics – Advanced Python

  • Spring-1 Elective: DSAN 5600: Applied Time Series for Data Science

  • Fall-2 Electives:

    • DSAN 6600: Neural Networks and Deep Learning

    • DSAN 5800: Advanced Natural Language Processing

  • Spring-2 Elective: DSAN 6850: NLP with Large Language Models

14.4 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

Example:

  • Fall-1 Elective: DSAN 6750: Geographic Information Systems (GIS) and Applications

  • Spring-1 Elective: DSAN 5900: Digital Storytelling

  • Fall-2 Electives:

    • DSAN 5700: Blockchain Technologies for Data Science

    • DSAN 6700: Machine Learning App Deployment

  • Spring-2 Electives:

    • DSAN 5600 (time-series) or DSAN 6800 (Cybersecurity)

14.5 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