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Program checklist · Minor

Data Science Minor

University of North Carolina Asheville · Asheville, NC

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
Minor
CIP
30.4901
Catalog edition
2026-2027
Checklist type
degree-program
Identifiers
IPEDS UNITID
199111
CourseShelf checklist
CK_199111_e27c6f1d
CollegeTransfer.Net
Institution Transfer Profile
Source
CourseShelf publish 61

Requirements to complete

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

Complete at least 24 hours, including

4 items
  1. CSCI 183
    Introduction to Programming: Data Science
    As published: “Introduction to Programming: Data Science (3)”
    3
  2. MATH 191
    Calculus I
    As published: “Calculus I (4)”
    4
  3. MATH 295
    Math for Machine Learning
    As published: “Math for Machine Learning (4)”
    4
  4. Note: MATH 291 and 365 can be substituted for MATH 295
    Not resolved to a course

One course from

5 items
  1. CSCI 329
    Big Data Analytics (STAT 329)
    As published: “Big Data Analytics (STAT 329) (3)”
    3
  2. CSCI 339
    Topics in AI and Machine Learning
    As published: “Topics in AI and Machine Learning (3)”
    3
  3. CSCI 427
    Data Science I (STAT 427)
    As published: “Data Science I (STAT 427) (3)”
    3
  4. STAT 329
    Big Data Analytics (CSCI 329)
    As published: “Big Data Analytics (CSCI 329) (3)”
    3
  5. STAT 427
    Data Science I (CSCI 427)
    As published: “Data Science I (CSCI 427) (3)”
    3

Either

2 items
  1. STAT 185
    Introductory Statistics
    As published: “Introductory Statistics (4)”
    4
  2. STAT 225
    Introduction to Calculus-Based Statistics
    As published: “Introduction to Calculus-Based Statistics (4)”
    4

Two additional courses from the following

15 items
  1. ASTR 420
    Observational Astronomy II
    As published: “Observational Astronomy II (3)”
    3
  2. ATMS 405
    Meteorological Statistics
    As published: “Meteorological Statistics (3)”
    3
  3. CSCI 329
    Big Data Analytics (STAT 329)
    As published: “Big Data Analytics (STAT 329) (3) (if not used previously)”
    3
  4. CSCI 339
    Topics in AI and Machine Learning
    As published: “Topics in AI and Machine Learning (3) (if not used previously)”
    3
  5. CSCI 343
    Database Management Systems
    As published: “Database Management Systems (3)”
    3
  6. CSCI 427
    Data Science I (STAT 427)
    As published: “Data Science I (STAT 427) (3) (if not used previously)”
    3
  7. ECON 365
    Econometrics
    As published: “Econometrics (4)”
    4
  8. POLS 396
    Quantitative Reasoning: Telling Stories with Numbers
    As published: “Quantitative Reasoning: Telling Stories with Numbers (4)”
    4
  9. STAT 325
    Introduction to Regression Models
    As published: “Introduction to Regression Models (3)”
    3
  10. STAT 326
    Statistics for Experimenters
    As published: “Statistics for Experimenters (3)”
    3
  11. STAT 329
    Big Data Analytics (CSCI 329)
    As published: “Big Data Analytics (CSCI 329) (3) (if not used previously)”
    3
  12. STAT 425
    Introduction to Probability Theory
    As published: “Introduction to Probability Theory (3)”
    3
  13. STAT 426
    Introduction to Mathematical Statistics
    As published: “Introduction to Mathematical Statistics (3)”
    3
  14. STAT 427
    Data Science I (CSCI 427)
    As published: “Data Science I (CSCI 427) (3) (if not used previously)”
    3
  15. STAT 428
    Data Science II
    As published: “Data Science II (3)”
    3

Additional Information

0 items
    Source. University of North Carolina Asheville, catalog 2026-2027 — https://catalog.unca.edu/preview_program.php?catoid=23&poid=4626. Captured page pages/0127.html.gz. Assembled from the institution's published catalog as captured; every record names its captured page and source URL. Assembled, not asserted.