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Academic Catalog 2021-2022

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  • Data Science, MS—Align

Data Science, MS—Align Program

2021-2022 Edition

  • Undergraduate
  • College of Professional Studies Undergraduate
  • Graduate
    • General Admission and Transfer Credit
    • Information for Entering Students
    • College Expenses
    • University-​Wide Academic Policies and Procedures
    • PhD Programs
    • College of Arts, Media and Design
    • D'Amore-​McKim School of Business
    • Khoury College of Computer Sciences
      • Academic Policies and Procedures
      • Computer Science
        • Computer Science, PhD
        • Artificial Intelligence, MS
        • Data Science, MS
        • Data Science, MS—Align
        • Robotics, MS
        • Computer Science, MSCS
        • Computer Science, MSCS—Align
        • Cloud Software Development, Graduate Certificate
        • Computer Science, Graduate Certificate
        • Data Analytics, Graduate Certificate
      • Cybersecurity
      • Health Informatics
      • Interdisciplinary
    • College of Engineering
    • Bouvé College of Health Sciences
    • School of Law
    • College of Professional Studies
    • College of Science
    • College of Social Sciences and Humanities
    • Gordon Institute of Engineering Leadership
    • Faculty
    • Appendix
  • Course Descriptions
  • Catalog Archives
  • Overview
  • Program Requirements

The innovative Align bridge program to the Master of Science in Data Science is designed for students with a BS/BA degree from all backgrounds. During the first semester of year one, students are expected to take foundational courses in computer science fundamentals, as well as a course in data structures/discrete mathematics. During their second semester, students will take coursework in programming for data science, as well as linear algebra and probability. Upon successful completion of the second semester, students in good standing will matriculate into the Master of Science in Data Science program.

The Master of Science in Data Science program is designed to give students a comprehensive framework for reasoning about data. Students will engage in extensive coursework intended to develop depth in data collection, storage, retrieval, manipulation, visualization, modeling, and interpretation. Students will also be able to choose elective courses from a variety of offerings in Khoury, the College of Engineering (COE), and throughout the campus to explore areas that generate data or specialized data science applications. Successful program graduates will be well-positioned to attain data scientist and data engineer positions in a fast-growing field or to progress into doctoral degrees in related disciplines.

Complete all courses and requirements listed below unless otherwise indicated.

Students should refer to the course numbering table for graduate course leveling.

Align Bridge Coursework

Students are required to complete all bridge courses unless otherwise determined by the program.

A grade of B or higher is required in each course.

Course List
Code Title Hours
Fundamentals
CS 5001
and CS 5003
Intensive Foundations of Computer Science
and Recitation for CS 5001
4
Discrete Structures
CS 5002Discrete Structures4
Programming for Data Science
DS 5010Introduction to Programming for Data Science4
Additional Align Coursework
DS 5020Introduction to Linear Algebra and Probability for Data Science4

Core Requirements

A cumulative GPA of 3.000 or higher is required in the following core courses:

Course List
Code Title Hours
Complete 20 semester hours from the following:
Algorithms
Complete 4 semester hours from the following:4
CS 5800
Algorithms
EECE 7205
Fundamentals of Computer Engineering
Data Management and Processing
DS 5110Introduction to Data Management and Processing4
Machine Learning and Data Mining
DS 5220Supervised Machine Learning and Learning Theory4
DS 5230Unsupervised Machine Learning and Data Mining4
Presentation and Visualization
DS 5500Capstone: Applications in Data Science4

Electives1

Course List
Code Title Hours
Complete 12 semester hours from the following:12
College of Computer and Information Science
CS 5100
Foundations of Artificial Intelligence
CS 5180
Reinforcement Learning and Sequential Decision Making
CS 5200
Database Management Systems
CS 5335
Robotic Science and Systems
CS 5340
Computer/Human Interaction
CS 5610
Web Development
CS 6120
Natural Language Processing
CS 6200
Information Retrieval
CS 6240
Large-Scale Parallel Data Processing
CS 6350
Empirical Research Methods
CS 6620
Fundamentals of Cloud Computing
CS 6650
Building Scalable Distributed Systems
CS 7140
Advanced Machine Learning
CS 7150
Deep Learning
CS 7180
Special Topics in Artificial Intelligence
CS 7200
Statistical Methods for Computer Science
DS 7990
Thesis
DS 7995
Project
CS 7280
Special Topics in Database Management
CS 7290
Special Topics in Data Science
College of Engineering
CIVE 7100
Time Series and Geospatial Data Sciences
CIVE 7388
Special Topics in Civil Engineering
EECE 5639
Computer Vision
EECE 5640
High-Performance Computing
EECE 5644
Introduction to Machine Learning and Pattern Recognition
EECE 7337
Information Theory
EECE 7370
Advanced Computer Vision
EECE 7397
Advanced Machine Learning
IE 7275
Data Mining in Engineering
IE 7280
Statistical Methods in Engineering
College of Social Sciences and Humanities
ECON 5140
Applied Econometrics
PPUA 5261
Dynamic Modeling for Environmental Decision Making
PPUA 5262
Big Data for Cities
PPUA 5263
Geographic Information Systems for Urban and Regional Policy
PPUA 5266
Urban Theory and Science
PPUA 7237
Advanced Spatial Analysis of Urban Systems
College of Science
ENVR 5563
Advanced Spatial Analysis
PHYS 5116
Complex Networks and Applications
PHYS 7305
Statistical Physics
PHYS 7321
Computational Physics
PHYS 7331
Network Science Data
Bouvé College of Health Sciences
PHTH 5202
Introduction to Epidemiology
PHTH 5210
Biostatistics in Public Health
PHTH 6224
Social Epidemiology
College of Arts, Media and Design
GSND 5110
Game Design and Analysis
GSND 6350
Data-Driven Player Modeling

Program Credit/GPA Requirements

40–48 total semester hours required
Minimum 3.000 GPA required

1

Students taking electives worth less than 4 credits (i.e., Bouvé courses) should enroll for an accompanying data science project course in the same semester to bring the cumulative credits to 4. In order to earn this additional credit, students are expected to work with faculty to design an additional project in line with the curricular aims of their chosen elective and the data science core learning outcomes.

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