Introduction
The Bachelor of Science in Applied Artificial Intelligence and Data Engineering (BSAAI) program is designed to equip students with the knowledge and skills needed to excel in the rapidly evolving fields of artificial intelligence (AI) and data engineering. The curriculum emphasizes the practical application of AI tools, data science methodologies, and engineering principles to solve real-world business problems.
Program Overview
Program curriculum focuses on preparing students for various roles, such as AI specialist, data engineer, machine learning engineer, data analyst, AI project manager, and more. Students participate in courses that are taught using active learning methods. Teaching techniques include lectures, class discussions, debates, student presentations, individual and group activities, creative assessments, various labs and assignments, real world projects and more. Additionally, students work individually and in teams on supervised projects in which they apply related concepts.
Program Objectives
Graduate of the Bachelor of Science in Applied Artificial Intelligence & Data Engineering (BSAAI) degree are expected to be able to:
- Demonstrate organizational proficiency and optimization in the application of AI tools and platforms.
- Demonstrate the application of machine learning models and algorithms.
- Understand and apply cloud-based AI services within the business framework.
- Apply data management techniques to extract, transform, load, and analyze data.
- Leverage project management techniques to align and optimize workflow.
- Assess the ethical implications of AI deployments in business and technology.
- Understand emergent AI trends, predictions, tools, and challenges.
- Demonstrate effective communication, problem-solving, and critical thinking skills.
- Demonstrate professionalism in communication, appearance, hygiene, and demeanor.
- Utilize technical and non-technical expertise in team-based, collaborative environments.
- Produce professional-quality specifications, models, and other documents.
- Effectively apply course objectives to personal and professional settings.
BSAAI Program Requirements
|
General Education Courses
|
45 Credits
|
|
Applied Artificial Intelligence & Data Engineering Core Courses
|
128 Credits
|
| Other Required Courses |
7 Credits |
|
Total Required for BS in Applied Artificial Intelligence & Data Engineering
|
180 Credits
|
General Education (45 credits)
Foundational Required Courses (23 credits)
| ENG110 | Introduction to English Composition | 4 credits |
| ENG210 | Persuasive & Professional Writing | 4 credits |
| FAC105 | Leadership & Problem Solving | 3 credits |
| FAC120 | Spoken Communications | 3 credits |
| FAC125 | Collaborative & Interpersonal Communications | 3 credits |
| HUM205 | Ethics | 3 credits |
| SSC101 | Educational Learning Theories | 3 credits |
Mathematics (9 credits)
Required courses:
| MAT101 | Mathematics for the Computer Sciences | 3 credits |
| MAT105 | College Algebra | 3 credits |
| MAT260 | Statistics | 3 credits |
Elective General Education (13 credits)
Complete an additional 13 credits from the following:
| ENG311 | Principles of Creative Writing | 2 credits |
| ENG312 | Creative Writing with AI | 1 credit |
| FAC101 | Art Appreciation | 2 credits |
| FAC130 | Character Design | 2 credits |
| FAC135 | 3D Printing | 2 credits |
| FAC201 | Music Appreciation | 2 credits |
| FAC210 | Music Composition | 2 credits |
| HUM160 | Ancient Mythology | 2 credits |
| HUM200 | The Imagination of Horror in Media | 2 credits |
| LIT110 | Science Fiction Through Literature | 2 credits |
| LIT120 | Comics as Literature | 2 credits |
| LIT130 | Literary Masters | 2 credits |
| LNG110 | Survey of Foreign Language | 2 credits |
| MAT125 | Geometry | 3 credits |
| MAT150 | Trigonometry | 3 credits |
| MAT200 | Math-Based Codes, Ciphers & Secrets | 3 credits |
| MAT210 | Linear Algebra | 3 credits |
| MAT250 | Calculus | 3 credits |
| MTM140 | Basics of Film | 2 credits |
| PSC115 | Introduction to Biology | 2 credits |
| PSC201 | Astronomy | 2 credits |
| PSC226 | Introductory Physics | 2 credits |
| PSC230 | Introduction to Chemistry | 2 credits |
| SSC150 | Introductory Psychology | 2 credits |
| SSC272 | United States Government | 2 credits |
| SSC322 | Conflict & Negotiation | 2 credits |
| SSC351 | Introduction to Intellectual Property | 2 credits |
Applied Artificial Intelligence & Data Engineering Courses (128 credits)
Introductory Core Courses (30 credits)
| AIE101 | Foundations of Artificial Intelligence | 4 credits |
| CSC105 | Using Modern Operating Systems | 2 credits |
| CSC110 | Introduction to Computer Science | 4 credits |
| CSC125 | Logical and Computational Thinking | 3 credits |
| CSC145 | Prompt Engineering | 1 credit |
| CSC150 | Object Oriented Programming & Design | 6 credits |
| CSC210 | Introduction to Web Presentation & Development | 2 credits |
| DBT130 | Databases I | 4 credits |
| ITH215 | Networking I | 2 credits |
| MGT101 | Introduction to Project Management | 2 credits |
Advanced Core Courses (69 credits)
| AAI110 | Applied AI Tools in Business | 3 credits |
| AAI350 | Cloud-Based AI Solutions | 3 credits |
| AAI380 | AI Governance & Compliance | 2 credits |
| AIE210 | Natural Language Processing | 3 credits |
| BIT370 | System Analysis & Business Modeling | 4 credits |
| BIT390 | Emerging Technologies in Business | 3 credits |
| BUS202 | Studies in Economics | 3 credits |
| BUS346 | Entrepreneurship | 4 credits |
| CSC181 | Scripting and Automation | 3 credits |
| DAT205 | Introduction to Data Science | 4 credits |
| DAT210 | Applied Data Analytics and Visualization | 3 credits |
| DAT220 | Applied Python for Data Analysis | 3 credits |
| DAT320 | Applied Machine Learning | 4 credits |
| DAT360 | Applied Data Engineering | 4 credits |
| DBT230 | Databases II | 4 credits |
| MOA141 | Introduction to Information Modeling | 3 credits |
And complete 16 credits from the following:
| AIE206 | Robotics | 4 credits |
| AIE306 | Computer Vision | 4 credits |
| CSC160 | Application Development | 4 credits |
| CSC180 | Open Source Platforms Development | 4 credits |
| CSC240 | Business Web Development | 4 credits |
| CSC260 | Dynamic Web Programming | 4 credits |
| CSC270 | Solution Stack Software Development | 3 credits |
| CSC280 | Developing Scalable Web Applications | 4 credits |
| MGT400 | Technology Leadership | 4 credits |
| PRO100 | Introductory Software Projects | 2 credits |
| TST200 | Quality Assurance I | 4 credits |
| TST270 | Quality Assurance II | 4 credits |
Project Core Courses (29 Credits)
| PRO110 | Applied AI Projects I (AI in Business) | 2 credits |
| PRO140 | Information Modeling Projects | 2 credits |
| PRO322 | Applied AI Projects II (Machine Learning) | 2 credits |
| PRO335 | Persistence Project | 2 credits |
| PRO361 | Applied AI Projects III (Data Engineering) | 2 credits |
| PRO382 | AI Certification Projects | 3 credits |
| PRO390 | Capstone Project | 4 credits |
| PRO490 | Enterprise Projects I | 6 credits |
| PRO492 | Enterprise Projects III | 6 credits |
Other Required Courses
Other Required Courses (7 credits)
| BUS101 | Personal Finance | 3 credits |
| BUS110 | Principles of Finance | 1 credit |
| NEU100 | College Success Strategies | 1 credits |
| NEU200 | Career Readiness | 2 credits |