Academic Tracks

A photo from University of Miami exhibitors at the eMerge Americas conference. A photo from University of Miami exhibitors at the eMerge Americas conference.

The Master of Science in Data Science (MSDS) program specialized areas of academic tracks for students wishing to narrow their field of study.

Technical Data Science

The academic track 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.

Accordion Group

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  • 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.

Smart Cities

The academic track 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.

Accordion Group

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  • 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 694 - GIS in Urban Design
    • ARC 684 - RAD LAB-UM
    • ARC 685 - 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.

Data Visualization

The academic track 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.

Accordion Group

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  • 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.

Marine and Atmospheric Science

The academic track in Marine and Atmospheric Science 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, Atmospheric, and Earth Sciences.

Accordion Group

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  • 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.

Educational Measurement and Statistics

The academic track in Educational Measurement and Statistics is for students who wish to pursue careers in independent research, test design and development, and the analysis and interpretation of large sums of quantitative data. Most courses in this concentration are taken within the College of Arts and Sciences' Departments of Computer Science and Mathematics, and the School of Education and Human Development.

Accordion Group

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  • Core - 9 Credits

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

  • Programming - 3 Credits

    Students must complete one of the following courses:

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

  • Mathematics & Statistics Courses - 9 Credits

    Students may choose from a variety of statistics courses from the Department of Mathematics or the Department of Education and Psychological Studies.

  • Data Science Applications - 6-9 Credits

    EPS 704 - Computer Applications in Educational and Behavioral Research

    EPS 707 - Item Response Theory

    EPS 711 - Advanced Topics in Research, Measurement, and Statistics

  • Internship, Capstone, or Project - 3-6 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.

Marketing

The academic track in Marketing is for students who wish to pursue careers in strategic branding, predictive analytics, market research, and consumer behavior. Most courses in this concentration are taken within the College of Arts and Sciences' Department of Computer Science and the Miami Herbert Business School.

Accordion Group

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  • Core - 9 Credits

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

  • Data Science Tools - 11 Credits

    • 3 Credits - Programming
    • 2 Credits - MKT 640: Foundations in Marketing Management
    • 2 Credits - MKT 641: Marketing Research and Decision Making
    • 2 Credits - MKT 646: Consumer Behavior
    • 2 Credits - MKT 675: Marketing Analytics

  • Data Science Applications - 6-8 Credits

    • 2 Credits - MKT 647: Advertising and Communications
    • 2 Credits - MKT 648: New Product Development
    • 2 Credits - MKT 649: Strategic Brand Marketing
    • 2 Credits - MKT 650: Strategic Marketing
    • 2 Credits - MKT 677: Strategic Digital Media Management

  • Internship, Capstone, or Project - 3-6 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.

Bioinformatics

The academic track in Bioinformatics is for students who wish to pursue careers in genomics, computational biology, and data analysis. Most courses in this concentration are taken within the College of Arts and Sciences' Department of Computer Science and the Department of Biology. 

Accordion Group

Open All Tabs
  • Core - 9 Credits

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

  • Data Science Tools - 11 Credits

    • 3 Credits - Programming
    Please contact j.baker2@miami.edu for more information regarding the remaining 8 credits that fulfill the Data Sciences Tool requirements.

  • Data Science Applications - 6-8 Credits

    Please contact j.baker2@miami.edu for more information regarding the remaining 6-8 credits that fulfill the Data Sciences Tool requirements.

  • Internship, Capstone, or Project - 3-6 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.

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