Artificial Intelligence, Bachelor of Science in Artificial Intelligence
Artificial Intelligence (AI) is a multidisciplinary field of computing that integrates principles from machine learning, natural language processing, computer vision, robotics, generative AI, and large language models (LLMs) to develop algorithms and software enabling machines to perform tasks that typically require human intelligence. As the field of AI continues its rapid advancement, it is pushing the boundaries of technological possibilities and is expected to be in great demand within the future workforce.
Artificial Intelligence, Bachelor of Science in Artificial Intelligence Requirements
A minimum of 120 credit hours is required for a Bachelor of Science degree in Artificial Intelligence. Thirty of the last 36 hours must be University of Nebraska at Omaha courses. Registering for courses without having taken the stated prerequisites could result in administrative withdrawal. Students must have a C or better grade in CIST 1400 and CSCI 1620 to serve as the prerequisite for all subsequent Computer Science (CSCI) courses. For all other courses applied towards the major, a grade of C- or better will meet the prerequisite and degree requirements.
To obtain an artificial intelligence degree, a student must fulfill the University General Education, College, and Departmental requirements. Some courses may satisfy requirements in more than one area, but credit is awarded only once, thereby reducing the total number of credit hours for the degree to 120. (This total does not include prerequisites.)
| Code | Title | Credits |
|---|---|---|
| GENERAL EDUCATION REQUIREMENTS - 34 Hours Required | ||
| Minimum of “C-“required | ||
| Fundamental Skills | 15 | |
Writing – 6 hrs. | ||
| ENGLISH COMPOSITION I | ||
| COLLEGE RESEARCH AND INFORMATION LITERACY | ||
Oral Communication – 3 hrs. | ||
| PUBLIC SPEAKING FUNDS | ||
or CMST 2120 | ARGUMENTATION AND DEBATE | |
Quantitative Literacy – 3 hrs. | ||
| INTRODUCTION TO MATHEMATICAL AND COMPUTATIONAL THINKING | ||
or MATH 1130 | QUANTITATIVE LITERACY | |
or MATH 1140 | QUANTITATIVE REASONING FOR HEALTHCARE PROFESSIONALS | |
or MATH 1300 | COLLEGE ALGEBRA WITH SUPPORT | |
Data Literacy – 3 hrs. | ||
Select one from the following: | ||
| DATA LITERACY AND VISUALIZATION | ||
| ELEMENTARY STATISTICS | ||
Until Fall 2028, students can satisfy this requirement with an approved data literacy course, or any approved natural or social science general education course. | ||
| Breadth of Knowledge | 13 | |
Social Science – 3 hrs. | ||
Humanities – 3 hrs. | ||
Natural & Physical Science (must complete a lab) – 4 hrs. | ||
Arts – 3 hrs. | ||
| Individual and Social Responsibility | 6 | |
Cultural Knowledge – 3 hrs. | ||
Civic Knowledge and Engagement – 3 hrs. | ||
| MAJOR REQUIREMENTS - 65 Hours Required | ||
| **Course will satisfy UNO's General Education requirement | ||
| ^Course requires pre-requisite(s) | ||
| All of the following: | 47 | |
| INTRODUCTION TO COMPUTER SCIENCE I (^) | ||
| INTRODUCTION TO COMPUTER SCIENCE II (^) | ||
| CALCULUS I (^) | ||
| MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE (^) | ||
| APPLIED LINEAR ALGEBRA (^) | ||
| CONCEPTS OF ARTIFICIAL INTELLIGENCE (^) | ||
| INTRODUCTION TO DATA ANALYTICS USING PYTHON (^) | ||
| INTRODUCTION TO APPLIED STATISTICS FOR IS&T (^) | ||
| TECHNICAL WRITING & COMMUNICATION FOR IS&T (^) | ||
| INFORMATION TECHNOLOGY ETHICS (** ^) | ||
| DATA STRUCTURES (^) | ||
| FUNDAMENTALS AND ALGORITHMS OF MACHINE LEARNING (^) | ||
| INTRODUCTION TO ALGORITHMS (^) | ||
| PRINCIPLES OF ARTIFICIAL INTELLIGENCE (^) | ||
AIML 4970 | AI CAPSTONE (^) | |
| Extension Courses – Complete 6 courses | 18 | |
Any CSCI courses numbered 2xxx-4xxxx which are not used to meet other BSAI degree requirements | ||
| SYMBOLIC LOGIC | ||
| BUSINESS INTELLIGENCE (^) | ||
| INTRODUCTION TO MACHINE LEARNING AND DATA MINING (^) | ||
| ELECTIVES | ||
| Elective hours as required to reach a total of 120 hours | ||
Artificial Intelligence, Bachelor of Science in Artificial Intelligence Four Year Plan - Start 1300-1200-1280
| First Year | ||
|---|---|---|
| Fall | Credits | |
| ENGL 1150 | ENGLISH COMPOSITION I | 3 |
| MATH 1950 | CALCULUS I | 5 |
| CMST 1110 or CMST 2120 | PUBLIC SPEAKING FUNDS or ARGUMENTATION AND DEBATE | 3 |
| CIST 1300 | INTRODUCTION TO WEB DEVELOPMENT or COMPUTER SCIENCE PRINCIPLES or INTRODUCTION TO COMPUTATIONAL SCIENCE | 3 |
| Elective course | 1 | |
| Credits | 15 | |
| Spring | ||
| ENGL 1160 | COLLEGE RESEARCH AND INFORMATION LITERACY | 3 |
| CIST 1400 | INTRODUCTION TO COMPUTER SCIENCE I | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Second Year | ||
| Fall | ||
| CSCI 1620 | INTRODUCTION TO COMPUTER SCIENCE II | 3 |
| CSCI 2030 | MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| AIML 2060 | CONCEPTS OF ARTIFICIAL INTELLIGENCE | 3 |
| CIST 2500 | INTRODUCTION TO APPLIED STATISTICS FOR IS&T | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Third Year | ||
| Fall | ||
| CSCI 2410 | INTRODUCTION TO DATA ANALYTICS USING PYTHON | 3 |
| CSCI 3320 | DATA STRUCTURES | 3 |
| CIST 3110 | INFORMATION TECHNOLOGY ETHICS | 3 |
| MATH 2050 | APPLIED LINEAR ALGEBRA | 3 |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| CSCI 3470 | FUNDAMENTALS AND ALGORITHMS OF MACHINE LEARNING | 3 |
| CSCI 4100 | INTRODUCTION TO ALGORITHMS | 3 |
| Extension Course | 3 | |
| Extension Course | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Fourth Year | ||
| Fall | ||
| CIST 3000 | TECHNICAL WRITING & COMMUNICATION FOR IS&T | 3 |
| CSCI 4450 | PRINCIPLES OF ARTIFICIAL INTELLIGENCE | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| AIML 4970 | Capstone | 3 |
| Extension Course | 3 | |
| Extension Course | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Total Credits | 120 | |
Artificial Intelligence, Bachelor of Science in Artificial Intelligence Four Year Plan- Start 1400
| First Year | ||
|---|---|---|
| Fall | Credits | |
| ENGL 1150 | ENGLISH COMPOSITION I | 3 |
| MATH 1950 | CALCULUS I | 5 |
| CMST 1110 or CMST 2120 | PUBLIC SPEAKING FUNDS or ARGUMENTATION AND DEBATE | 3 |
| CIST 1400 | INTRODUCTION TO COMPUTER SCIENCE I | 3 |
| Elective Course | 1 | |
| Credits | 15 | |
| Spring | ||
| ENGL 1160 | COLLEGE RESEARCH AND INFORMATION LITERACY | 3 |
| CSCI 1620 | INTRODUCTION TO COMPUTER SCIENCE II | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Second Year | ||
| Fall | ||
| CSCI 2030 | MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE | 3 |
| AIML 2060 | CONCEPTS OF ARTIFICIAL INTELLIGENCE | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| CSCI 3320 | DATA STRUCTURES | 3 |
| CIST 2500 | INTRODUCTION TO APPLIED STATISTICS FOR IS&T | 3 |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Third Year | ||
| Fall | ||
| CIST 3110 | INFORMATION TECHNOLOGY ETHICS | 3 |
| CSCI 2410 | INTRODUCTION TO DATA ANALYTICS USING PYTHON | 3 |
| MATH 2050 | APPLIED LINEAR ALGEBRA | 3 |
| Extension Course | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| CSCI 3470 | FUNDAMENTALS AND ALGORITHMS OF MACHINE LEARNING | 3 |
| CSCI 4100 | INTRODUCTION TO ALGORITHMS | 3 |
| CIST 3000 | TECHNICAL WRITING & COMMUNICATION FOR IS&T | 3 |
| Extension Course | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Fourth Year | ||
| Fall | ||
| CSCI 4450 | PRINCIPLES OF ARTIFICIAL INTELLIGENCE | 3 |
| Extension Course | 3 | |
| Extension Course | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Spring | ||
| AIML 4970 | Capstone | 3 |
| Extension Course | 3 | |
| Extension Course | 3 | |
| General Education Course or Elective | 3 | |
| General Education Course or Elective | 3 | |
| Credits | 15 | |
| Total Credits | 120 | |