Information Science: Data Science Emphasis

Program Overview

Information Science: Data Science Emphasis

Overview

The Information Science: Data Science Emphasis program is designed to equip students with the skills and knowledge necessary to collect, manipulate, and analyze different types of data at various scales. The program focuses on the application of computational thinking, data analysis, and interpretation to real-world problems.

Learning Outcomes

• Students will demonstrate the ability to conduct a research project using appropriate and ethical methods, including proper citation of sources.
• Students will establish the ability to exercise the four key techniques of computational thinking (decomposition, pattern recognition, abstraction, and algorithms) in solving information and data challenges.
• Students will acquire the skills of collecting, manipulating, and analyzing different types of data at different scales, and interpreting the results properly.
• Students will be able to recognize and analyze ethical and policy concerns raised by new technologies and will be able to apply ethical thinking to real-world cases and craft effective solutions.
• Students will be able to identify and apply professional ethics and standards relevant to their career aspirations.
• Students will demonstrate understanding of the use of information and communication technologies and the implications of such use, for example: scientific and social uses of information, and social, cultural, and economic implications of digital life and culture.
• Students will demonstrate facility using basic research methods, for example: research design; statistics and analysis; organization, identification, and location of data and information including open- and closed-access sources; and/or presentation of findings in oral, written and multi-media form, including proper use of and citation of sources.
• Students will acquire the skills, knowledge, and self-understanding to communicate with and effectively work and interact across cultures and with diverse people and groups.
• Students will demonstrate knowledge of career and further education options and opportunities open to them relative to their plan of study and will set goals and make plans beyond their expected graduation.

Program Details

Coursework Location(s)

• Main/Tucson
• North Kazakhstan University

Areas of Interest

• Computer & Information Science
• Engineering & Technology
• Interdisciplinary Studies
• Mathematics, Statistics & Data Science

Level of Math

• Moderate Knowledge

The M-strand is for students who require mathematical facility at the level of at least MATH 112 (College Algebra Concepts) or 108 (Modeling with Algebraic and Trigonometric Functions). This strand involves reasonable facility with algebra and algebraic functions, graphs, and simple modeling. Students who choose the M-strand are prepared for further mathematical work. This work may include MATH 107 (Exploring and Understanding Data), MATH 113 (Elements of Calculus), MATH 116 (Calculus Concepts for Business), MATH 119A (Mathematics of Biological Systems: A Calculus Based Approach), or a statistics class from outside the Mathematics Department, such as ISTA 116 (Statistical Foundations for the Information Age) or SBS 200 (Statistics for the Social Sciences).

Level of Second Language

• 2nd Semester Proficiency

Second-semester skill level in a second language is required. Non-B.A. degree students may fulfill this requirement with one of the following options: 1. Scoring the equivalent of second-semester skill level on an entrance or placement examination administered by The University of Arizona. 2. Completion with a C or better of a second semester course at the post-secondary level. 3. An AP (Advanced Placement), IB (International Baccalaureate) or CLEP (College Level Entrance Program) language score determined by the individual language department. 4. In the College of Engineering by a method determined within the College; however, all students in the college must also take a language placement examination on entrance to the University.

Pre-major Required?

• No

This Major's College

• College of Information Science

Degree

• Bachelor of Science

Sample Plans

2025, Information Science: Data Science Emphasis

• 4-Year Sample Plan
• Map Transfer Coursework

First Year

1st Semester

• ENGL 101 - First Year Writing 1 (3 credits)
• GE Foundation Mathematics (3 credits)
• Second Language (First Semester) (4 credits)
• GE Core: Exploring Perspectives or Building Connections (3 credits)
• GE Core: Exploring Perspectives or Building Connections (3 credits)
• Introduction to the General Education Experience (Entry Course) (1 credit)

2nd Semester

• ENGL 102 - First Year Writing 2 (3 credits)
• Second Language (Second Semester) (4 credits)
• GE Core: Exploring Perspectives or Building Connections (3 credits)
• GE Core: Exploring Perspectives or Building Connections (3 credits)
• GE Core: Exploring Perspectives or Building Connections (3 credits)

Second Year

3rd Semester

• GE Core: Exploring Perspectives or Building Connections (3 credits)
• GE Core: Exploring Perspectives or Building Connections (3 credits)
• ISTA 100 (3 credits)
• ISTA 116 (3 credits)
• ISTA 130 (3 credits)
• General Education Portfolio (Exit Course) (1 credit)

4th Semester

• ISTA 131 (3 credits)
• ISTA 161 (3 credits)
• ESOC 302 (3 credits)
• Minor Course (3 credits)
• Minor Course (3 credits)

Third Year

5th Semester

• Computational Arts (3 credits)
• Society (3 credits)
• Emphasis Course (3 credits)
• Minor Course (3 credits)
• General Elective (3 credits)

6th Semester

• Emphasis Course (3 credits)
• Emphasis Course (3 credits)
• Minor Course (3 credits)
• Minor Course (3 credits)
• General Elective (3 credits)

Fourth Year

7th Semester

• Emphasis Course (3 credits)
• Emphasis Course (3 credits)
• Minor Course (3 credits)
• General Elective (3 credits)
• General Elective (3 credits)

8th Semester

• ISTA 498: Senior Capstone (3 credits)
• ESOC 480 or Engagement Course (3 credits)
• General Elective (3 credits)
• General Elective (3 credits)
• General Elective (3 credits)