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Undergraduate Requirements Archive → 2025/2026 Undergraduate Requirements - under construction → B.S. in Data Science - under construction

4. B.S. in Data Science - under construction

The information and requirements given here apply to the 2025–2026 catalog. For other catalog years, please consult the archive. This major is new as of 2025.

Data Science Supporting Requirements

The following requirements are part of the B.S. (Bachelor of Science) degree, but as supporting requirements, do not count in the major units or GPA.

Language Requirement

Students must demonstrate second semester proficiency in a second language for the B.S. degree.

Laboratory Science Requirement

The degree is science-intensive and requires two of the following lab science courses:

• First-semester courses (no prerequisites other than mathematics): PHYS 141, PHYS 161H, CHEM 151, CHEM 141 & (143 or 145)^(*), CHEM 161 & 163^(*), CHEM 181, MCB 181R & 181L^(*), ECOL 182R & 182L^(*), PSIO 201, GEOS 251, HWRS 350, PHYS 102 & 181^(*), PHYS 110

• Courses that require one or more science prerequisites: PHYS 142, PHYS 241, PHYS 162H, PHYS 261H, CHEM 152, CHEM 142 & (144 or 146)^(*), CHEM 162 & 164^(*), CHEM 182,  ENVS 200 & ENVS 201^(**), PSIO 202, GEOS 255, GEOS 302, GEOS 304, GEOS 308, GEOS 322, MSE 110, PHYS 103
  & 182^(*), PHYS 111

^(*) Lecture and lab must both be taken to constitute one lab science course.

^(**) Lecture and lab must both be taken to constitute one lab science course. This option was not approved in time to get into the official requirements for Fall 2025; students from any catalog math email the Math Center to have the adjustment made to their requirements: math-mathcenter@arizona.edu

Minor Optional

A minor is optional for the B.S. in Data Science

Data Science Major Requirements

Data Science Major Emphases

The B.S. in Data Science requires a core of basic courses followed by additional courses specific to one of the emphases detailed below. There are currently four emphases available to Main campus students and one for our partner campus at CUEB in Beijing, China; additional Main campus emphases may be added in future.

• Applied Statistics Emphasis: This emphasis is for students who intend to work in industry as a Data Scientist upon graduation.
• Comprehensive Statistics Emphasis: This emphasis prepares students for graduate study in data science, probability and statistics, and related fields.
• Computing Emphasis:
• Molecular and Cellular Biology Emphasis:
• Global Emphasis: This emphasis is offered only at our partner university, Capital University of Economics and Business, in Beijing, China. 

Data Science Core Courses

The following courses are required for all Data Science majors:

• Choose one:⁽¹⁾
  • CSC 110 — Introduction to Computer Programming I OR
  • ISTA 130 — Computational Thinking and Doing
• Choose one:⁽¹⁾
  • CSC 120 — Introduction to Computer Programming II OR
  • ISTA 131 — Dealing With Data
• MATH 122A AND MATH 122B⁽²⁾ or MATH 125 — Calculus I
• MATH 129 — Calculus II
• DATA 201 — Foundations of Data Science⁽³⁾
• MATH 263 — Introduction to Statistics & Biostatistics
• MATH 313 — Introduction to Linear Algebra⁽⁴⁾

⁽¹⁾ ISTA 131 will not substitute for CSC 120 as a prerequisite to future CSC courses for students selecting the Computing emphasis.
⁽²⁾ MATH 122A and MATH 122B are a single-semester sequence of courses that cover Calculus I.
⁽³⁾ DATA 201 is a new Building Connections Gen Ed. It was first offered in Spring 2025.
⁽⁴⁾ Students who have transfer credit equivalent to MATH 215 may use it to fulfill this requirement, though they will not earn upper-division credit for the course.

Applied Statistics Emphasis

• Core Courses (see above)
• ISTA 322 — Data Engineering⁽¹⁾
• DATA 363 — Introduction to Statistical Methods
• DATA 375 — Introduction to Statistical Computing
• DATA 467 — Introduction to Applied Regression and Generalized Linear Models
• DATA 474 — Introduction to Statistical Machine Learning
• DATA 498A — Capstone for Statistics & Data Science
• Choose one of the following 1-unit opportunities:
  • DATA 195M — Math and SDS Major Colloquium
  • DATA 395M — Career Exploration in Mathematics and Data Science
  • DATA 391 or 491 — Preceptorship
  • DATA 393 or 493 — Internship
• Choose four (4) electives from the following:
  • MATH 223 — Vector Calculus (4 units)
  • ISTA 320 — Data Visualization
  • ISTA 321 — Data Mining and Discovery
  • DATA 367 — Statistical Methods in Sports Analytics
  • DATA 396T or 496T — Topics in Undergraduate Statistics & Data Science⁽²⁾
  • ISTA 410 — Bayesian Modeling and Inference
  • MCB 416 — Bioinformatics and Functional Genomic Analysis
  • DATA/LING 439 — Statistical Natural Language Processing
  • SIE 440 — Survey of Optimization Methods
  • MCB 447 — Big Data in Molecular Biology and Biomedicine
  • DATA/MATH 462 — Financial Math
  • MATH 464 — Theory of Probability
  • DATA 492 — Directed Research⁽³⁾
  • DATA 498H — Honors Thesis⁽³⁾

⁽¹⁾ CSC 460 Database Design will also fulfill this requirement, but has additional prerequisites.
⁽²⁾ DATA 396T and 496T are special topics courses. When available, they will usually be offered in spring, and topics covered will vary. Consult an advisor for details and availability.
⁽³⁾ Three units of DATA 492 or 498H may apply to this requirement; 498H is restricted to Honors College members.

Comprehensive Statistics Emphasis

• Core Courses (see above)
• MATH 223 — Vector Calculus
• ISTA 322 — Data Engineering⁽¹⁾
• DATA 363 — Introduction to Statistical Methods
• DATA 375 — Introduction to Statistical Computing
• MATH 464 — Theory of Probability 
• MATH 466 — Theory of Statistics
• DATA 467 — Introduction to Applied Regression and Generalized Linear Models
• DATA 474 — Introduction to Statistical Machine Learning
• DATA 498A — Capstone for Statistics & Data Science
• Choose one elective from the following:
  • MATH 323 — Formal Mathematical Reasoning & Writing
  • DATA 367 — Statistical Methods in Sports Analytics
  • DATA 396T — Topics in Undergraduate Statistics & Data Science⁽²⁾
  • DATA/MATH 412 — Linear Algebra for Data Science
  • SIE 440 — Survey of Optimization Methods
  • DATA/MATH 462 — Financial Math
  • MATH 468 — Applied Stochastic Processes
  • DATA 496T — Advanced Topics in Undergraduate Statistics & Data Science⁽²⁾
  • DATA 498H — Honors Thesis⁽³⁾

⁽¹⁾ CSC 460 Database Design will also fulfill this requirement, but has additional prerequisites.
⁽²⁾ DATA 396T and 496T are special topics courses. When available, they will usually be offered in spring, and topics covered will vary. Consult an advisor for details and availability.
⁽³⁾ Three units of DATA 492 or DATA 498H may apply to this requirement; DATA 498H is restricted to students in the Franke Honors College.

Computing Emphasis

• Core Courses (see above)
• CSC 144 — Discrete Math for Computer Science I⁽¹⁾
• CSC 210 — Software Development
• CSC 244 — Discrete Math for Computer Science II
• CSC 335 — Object-Oriented Programming and Design
• CSC 345 — Analysis of Discrete Structures
• CSC 380 — Principles of Data Science⁽²⁾
• DATA 375 — Introduction to Statistical Computing
• CSC 460 — Database Design
• CSC 480 — Principles of Machine Learning
• DATA 498A — Capstone for Statistics & Data Science

⁽¹⁾ MATH 243 will also fulfill this requirement.
⁽²⁾ DATA/MATH 363 will also fulfill this requirement.

Molecular & Cellular Biology Emphasis

• Core Courses (see above)
• MCB 181R — Introductory Biology I
• ISTA 322 — Data Engineering⁽¹⁾
• MCB 330 — Critical Reasoning and Problem Solving in Biomedicine
• DATA 363— Introduction to Statistical Methods
• DATA 375 — Introduction to Statistical Computing
• MCB 404 — Bioethics
• Choose one:
  • MCB 410 — Cell Biology
  • MCB 411 — Molecular Biology
  • MCB 416A — Bioinformatics & Functional Genome Analysis
  • MCB 447 — Big Data in Molecular Biology & Biomedicine
  • MCB 480 — Introduction to Systems Biology
  • MCB 489 — Foundations of Synthetic Biology
• Choose one capstone:
  • DATA 498A — Capstone for Statistics & Data Science
  • MCB 498 — Capstone

⁽¹⁾ CSC 460 Database Design will also fulfill this requirement, but has additional prerequisites.

Global Emphasis

• Core Courses (see above)
• MATH 223 — Vector Calculus
• ISTA 322 — Data Engineering
• DATA 363 — Introduction to Statistical Methods
• DATA 375 — Introduction to Statistical Computing
• MATH 464 — Theory of Probability
• MATH 466 — Theory of Statistics
• DATA 467 — Introduction to Applied Regression and Generalized Linear Models
• DATA 474 — Introduction to Statistical Machine Learning
• DATA 498A — Capstone for Statistics & Data Science
• DATA 499 — Independent Study (thesis)⁽¹⁾

⁽¹⁾ Students at the CUEB campus will enroll in thesis units through their home university that will be used to fulfill
this requirement.