Concentrations

The concentration in Technical Data Science is for students who wish to pursue careers in machine learning, data mining, data engineering, programming, and big data analytics.  Most courses in this concentration are taken within the College of Arts and Sciences’ Departments of Computer Science and Mathematics, and the College of Engineering.

• Core - 9 Credits

  • 3 Credits - Machine Learning or Data Mining
  • 3 Credits - Data Visualization
  • 3 Credits - Statistics

• Data Science Tools - 12 Credits

  • 3 Credits - Programming
  • 3 Credits - Database Systems
  • 3 Credits - Data Analysis
  • 3 Credits - Statistics

• Data Science Applications - 6 Credits

  At least 6 credits of data science applications courses must be taken (some tracks may specify additional courses).

• Internship, Project, or Capstone - 3 Credits

  Internship: This is a three- or six-month internship. Three-month internships are for 3 credits, and are done in either semester or the summer. Six-month internships are for 6 credits, and are done either from spring to summer or from summer to fall.  The internship culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Project: This is a semester long individual or small group project for 3 or 6 credits, depending on the scope of the project. Projects are done within one or two semesters. The student will be supervised by a faculty member within an appropriate academic unit in the program. The project culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Capstone: This is a 3 credit culminating course, integrating the knowledge and experience gained in the more specific courses of a track. The course will normally be offered by one of the units that provides the track. It may include lectures, surveys, project work, and other components.

The concentration in Smart Cities is for students who wish to pursue careers in urban planning and design, information and communication technology, the internet of things, and sustainable built environments.  Most courses in this concentration are taken within the School of Architecture.

• Core - 9 Credits

  • 3 Credits - Machine Learning or Data Mining
  • 3 Credits - Data Visualization
  • 3 Credits - Statistics

• Data Science Tools - 9 Credits

  • 3 Credits - Programming
  • 6 Credits - Either additional Programming courses, Database Systems, Data Visualization, Machine Learning and Data Mining, or Mathematics and Statistics courses.

• Data Science Applications - 9 Credits

  • ARC 594 - GIS in Urban Design
  • ARC 694 - RAD LAB-UM
  • ARC 686 - BIM/Virtual Design and Construction

• Internship, Project, or Capstone - 3 Credits

  Internship: This is a three- or six-month internship. Three-month internships are for 3 credits, and are done in either semester or the summer. Six-month internships are for 6 credits, and are done either from spring to summer or from summer to fall.  The internship culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Project: This is a semester long individual or small group project for 3 or 6 credits, depending on the scope of the project. Projects are done within one or two semesters. The student will be supervised by a faculty member within an appropriate academic unit in the program. The project culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Capstone: This is a 3 credit culminating course, integrating the knowledge and experience gained in the more specific courses of a track. The course will normally be offered by one of the units that provides the track. It may include lectures, surveys, project work, and other components.

The concentration in Data Visualization is for students who wish to pursue careers in intelligence analytics, visual journalism, infographic design, interactive media, and geospatial technology.  Most courses in this concentration are taken within the School of Communication and the College of Arts & Sciences’ Department of Geography and Regional Studies.

• Core - 9 Credits

  • 3 Credits - Machine Learning or Data Mining
  • 3 Credits - Data Visualization
  • 3 Credits - Statistics

• Data Science Tools - 9 Credits

  • 3 Credits - Programming
  • 6 Credits - Either additional Programming courses, Database Systems, Data Visualization, Machine Learning and Data Mining, or Mathematics and Statistics courses.

  *Students interested in spatial visualization may choose to take their remaining 6 credits from the following:

  • GEG 691 - Geographic Information Systems I
  • GEG 692 - Geographic Information Systems II
  • GEG 680 - Spatial Data Analysis I 
  • GEG 681 - Spatial Data Analysis II

   

• Data Science Applications - 9 Credits

  Students must complete the following courses:

  • CSC 688 - Data Science and Visualization
  • JMM 622 - Introduction to Infographics
  • JMM 692 - Interactive Data Visualization for the Web

• Internship, Project, or Capstone - 3 Credits

  Internship: This is a three- or six-month internship. Three-month internships are for 3 credits, and are done in either semester or the summer. Six-month internships are for 6 credits, and are done either from spring to summer or from summer to fall.  The internship culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Project: This is a semester long individual or small group project for 3 or 6 credits, depending on the scope of the project. Projects are done within one or two semesters. The student will be supervised by a faculty member within an appropriate academic unit in the program. The project culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Capstone: This is a 3 credit culminating course, integrating the knowledge and experience gained in the more specific courses of a track. The course will normally be offered by one of the units that provides the track. It may include lectures, surveys, project work, and other components.

The concentration in Marine and Atmospheric Sciences is for students who wish to pursue careers in climatology and meteorology, ocean sciences, hydrography, and applied remote sensing.  Most courses in this concentration are taken within the Rosenstiel School of Marine and Atmospheric Science.

• Core - 9 Credits

  • 3 Credits - Machine Learning or Data Mining
  • 3 Credits - Data Visualization
  • 3 Credits - Statistics

• Data Science Tools - 3 Credits

  Students must complete the following courses:

  • CSC 686 - Programming in Python for Scientists
  • CSC 632 - Introduction to Parallel Computing
  • CSC 640 - Algorithm Design and Analysis

• Data Science Applications - 15 Credits

  Students must complete the following courses:

  • OCE 642 - Physics of Remote Sensing I: Passive Systems
  • OCE 686 - Applied Remote Sensing
  • OCE 642 - Physics of Remote Sensing II: Active Systems
  • OCE 687 - Applied Radar Remote Sensing
  • MES 660 - Introduction to Marine Geographic Information Systems
  • MES 661 - GIS Laboratory

  *Or any other courses selected from the concentration course lists for the RSMAS Master of Professional Science (MPS) with advisor approval

• Internship, Project, or Capstone - 3 Credits

  Internship: This is a three- or six-month internship. Three-month internships are for 3 credits, and are done in either semester or the summer. Six-month internships are for 6 credits, and are done either from spring to summer or from summer to fall.  The internship culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Project: This is a semester long individual or small group project for 3 or 6 credits, depending on the scope of the project. Projects are done within one or two semesters. The student will be supervised by a faculty member within an appropriate academic unit in the program. The project culminates with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.

  Capstone: This is a 3 credit culminating course, integrating the knowledge and experience gained in the more specific courses of a track. The course will normally be offered by one of the units that provides the track. It may include lectures, surveys, project work, and other components.