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Program checklist · BS

Data Science, BS

Longwood University · Farmville, VA

A checklist is the list of requirements to complete this program and receive the award, as the college publishes it in its catalog. It is the same for everyone. It does not say what you have completed; that comes from applying your own record.

Program
Award
BS
Credential class
ceterms:BachelorDegree
Total credits (published)
120
Catalog edition
2026-2027
Checklist type
degree-program
Identifiers
IPEDS UNITID
232566
CourseShelf checklist
CK_232566_3fc948e1
CollegeTransfer.Net
Institution Transfer Profile
Source
CourseShelf publish 59

Requirements to complete

Every course or condition the catalog lists, in the catalog's order.

Civitae Core Curriculum (39-40 credits)

2 items
  1. Data Science majors are required to take MATH 171 , which satisfies the Quantitative Reasoning Pillar requirement.
    Not resolved to a course
  2. Data Science majors are required to take MATH 301 , which satisfies the Quantitative Reasoning Perspective requirement.
    Not resolved to a course

Additional Degree Requirements (3-4 credits)

1 item
  1. Any natural or social science course, excluding MATH and CMSC courses for 3-4 credits
    Not resolved to a course

Major Requirements (55-58 credits + 6 credits counted in Civitae)

0 items

    Computer Science Core (18 credits)

    6 items
    1. CMSC 140
      Introduction to Programming
      As published: “Introduction to Programming 3 credits”
      3
    2. CMSC 160
      Introduction to Algorithmic Design I
      As published: “Introduction to Algorithmic Design I 4 credits”
      4
    3. CMSC 161
      Software Development Tools and Principles
      As published: “Software Development Tools and Principles 1 credit”
      1
    4. CMSC 162
      Introduction to Algorithmic Design II
      As published: “Introduction to Algorithmic Design II 4 credits”
      4
    5. CMSC 262
      Data Structures and Algorithms in Application
      As published: “Data Structures and Algorithms in Application 3 credits”
      3
    6. CMSC 317
      Applied Machine Learning
      As published: “Applied Machine Learning 3 credits”
      3

    Data Science Core (14 credits)

    6 items
    1. DATA 102
      Introduction to Data Science: The Data Life-Cycle
      As published: “Introduction to Data Science: The Data Life-Cycle 3 credits”
      3
    2. DATA 282
      Experiential Learning Seminar in Data Science
      As published: “Experiential Learning Seminar in Data Science 1 credit”
      1
    3. DATA 350
      Ethical Issues in Data Science
      As published: “Ethical Issues in Data Science 3 credits”
      3
    4. DATA 481
      Practice of Data Science Consulting I
      As published: “Practice of Data Science Consulting I 2 credits”
      2
    5. DATA 482
      Practice of Data Science Consulting II
      As published: “Practice of Data Science Consulting II 2 credits”
      2
    6. ENGL 319
      Technical Writing
      As published: “Technical Writing 3 credits”
      3

    Mathematics and Statistics Core (14 credits + 6 credits counted in Civitae)

    6 items
    1. MATH 171
      Statistical Decision Making
      As published: “Statistical Decision Making 3 credits”
      3
    2. MATH 175
      Discrete Mathematics
      As published: “Discrete Mathematics 3 credits”
      3
    3. MATH 250
      Linear Algebra
      As published: “Linear Algebra 3 credits”
      3
    4. MATH 261
      The Differential and Integral Calculus I
      As published: “The Differential and Integral Calculus I 4 credits”
      4
    5. MATH 262
      The Differential and Integral Calculus II
      As published: “The Differential and Integral Calculus II 4 credits”
      4
    6. MATH 301
      Applied Statistics
      As published: “Applied Statistics 3 credits”
      3

    Major Electives (9-12 credits)

    12 items
    1. CMSC 387
      Introduction to Machine Learning
      As published: “Introduction to Machine Learning 3 credits”
      3
    2. CMSC 389
      Artificial Intelligence
      As published: “Artificial Intelligence 3 credits”
      3
    3. ECON 414
      Econometrics and Forecasting
      As published: “Econometrics and Forecasting 3 credits”
      3
    4. GEOG 358
      Map Design and Analysis
      As published: “Map Design and Analysis 4 credits”
      4
    5. GEOG 383
      Introduction to Remote Sensing
      As published: “Introduction to Remote Sensing 4 credits”
      4
    6. GEOG 430
      Geospatial Modeling and Analysis
      As published: “Geospatial Modeling and Analysis 4 credits”
      4
    7. MATH 275
      Probability & Bayesian Statistics I
      As published: “Probability & Bayesian Statistics I 3 credits”
      3
    8. MATH 331
      Survey Instrument Design & Analysis
      As published: “Survey Instrument Design & Analysis 3 credits”
      3
    9. MATH 372
      Mathematical Probability and Statistics I
      As published: “Mathematical Probability and Statistics I 3 credits”
      3
    10. MATH 373
      Experimental Design & Statistical Analysis
      As published: “Experimental Design & Statistical Analysis 3 credits”
      3
    11. MATH 375
      Probability & Bayesian Statistics II
      As published: “Probability & Bayesian Statistics II 3 credits”
      3
    12. MATH 472
      Mathematical Probability and Statistics II
      As published: “Mathematical Probability and Statistics II 3 credits”
      3

    General Electives (18-23 credits)

    0 items
      Source. Longwood University, catalog 2026-2027 — https://catalog.longwood.edu/preview_program.php?catoid=19&poid=2948. Captured page pages/0086.html.gz. Assembled from the institution's published catalog as captured; every record names its captured page and source URL. Assembled, not asserted.