Bachelor of Science in AI Software and Systems Engineering
September 29, 2026 2026-09-29 3:33Bachelor of Science in AI Software and Systems Engineering
A program that prepares students to design, develop, integrate, and maintain intelligent software systems that leverage artificial intelligence to solve complex technical and organizational challenges. The program combines software engineering, artificial intelligence, computer science, systems engineering, cloud computing, cybersecurity, data engineering, and human-centered design to provide graduates with the knowledge and technical skills needed to build reliable, scalable, and ethical AI-driven software solutions.
Bachelor of Science (B.S.) in AI Software and Systems Engineering
US$ 7,360
3–4 Years — Traditional Learning Track
9–12 Months — Fast-Track Learning Program
3–4 Years
9–12 Months
3 Credit Hours
US$ 7,360
Build Reliable, Scalable, and Ethical AI-Driven Software Systems
A project-based curriculum emphasizing software architecture, intelligent application development, machine learning integration, systems analysis, software quality assurance, DevOps, cloud-native development, and AI governance.
The Bachelor of Science in AI Software and Systems Engineering prepares students to design, develop, integrate, and maintain intelligent software systems that leverage artificial intelligence to solve complex technical and organizational challenges. The program combines software engineering, artificial intelligence, computer science, systems engineering, cloud computing, cybersecurity, data engineering, and human-centered design to provide graduates with the knowledge and technical skills needed to build reliable, scalable, and ethical AI-driven software solutions.
Structured in the style of leading U.S. universities, the curriculum emphasizes software architecture, intelligent application development, machine learning integration, systems analysis, software quality assurance, DevOps, cloud-native development, and AI governance. Through project-based learning, collaborative software development, and applied research, students gain experience in the full software development lifecycle while incorporating AI technologies into enterprise and emerging digital systems.
The program prepares graduates for careers as AI software engineers, software systems engineers, machine learning engineers, intelligent systems developers, full-stack AI developers, cloud AI engineers, data engineers, DevOps engineers, AI solutions architects, enterprise software developers, AI applications engineers, and software quality engineers. It also provides excellent preparation for graduate study in AI Software Engineering, Computer Science, Machine Learning, Systems Engineering, and related disciplines.
Bachelor of Science (B.S.) in AI Software and Systems Engineering
3–4 Years — Traditional Learning Track
9–12 Months — Fast-Track Learning Program
3 Credit Hours per Course
US$ 7,360
Exclusive of applicable University administrative fees
Required Major Courses
The major consists of coursework in programming, data structures, software engineering, databases, machine learning, AI algorithms, software architecture, cloud computing, cybersecurity, human-computer interaction, IoT, natural language processing, computer vision, systems analysis, quality assurance, AI ethics, agile project management, and enterprise AI. Students also complete the University's General Education requirements together with approved elective coursework.
| Course No. | Course Title | Credits |
|---|---|---|
| AISE 3000 | Introduction to AI Software and Systems Engineering | 3 |
| AISE 3010 | Programming Fundamentals for AI Systems | 3 |
| AISE 3020 | Data Structures and Algorithm Design | 3 |
| AISE 3030 | Software Engineering Principles | 3 |
| AISE 3040 | Database Systems and Data Engineering | 3 |
| AISE 3050 | Machine Learning for Software Engineers | 3 |
| AISE 3060 | Artificial Intelligence Algorithms | 3 |
| AISE 3070 | Software Architecture and Design | 3 |
| AISE 3080 | Cloud Computing and DevOps | 3 |
| AISE 3090 | Cybersecurity for AI Systems | 3 |
| AISE 3100 | Human-Computer Interaction | 3 |
| AISE 3110 | Internet of Things and Intelligent Systems | 3 |
| AISE 3120 | Natural Language Processing Applications | 3 |
| AISE 3130 | Computer Vision Systems | 3 |
| AISE 3140 | Systems Analysis and Integration | 3 |
| AISE 3150 | Software Quality Assurance and Testing | 3 |
| AISE 3160 | AI Ethics, Governance, and Compliance | 3 |
| AISE 3170 | Agile Project Management for AI Development | 3 |
| AISE 3180 | Enterprise AI Applications | 3 |
| AISE 3190 | Capstone Project in AI Software and Systems Engineering | 6 |
| Total Credits | 63 | |
Course Descriptions
Select a course to view its description.
AISE 3000 – Introduction to AI Software and Systems Engineering
Introduces the principles of software engineering, intelligent systems, artificial intelligence applications, and systems thinking in modern software development.
AISE 3010 – Programming Fundamentals for AI Systems
Develops programming skills using modern programming languages, emphasizing object-oriented design, algorithms, debugging, and software development best practices.
AISE 3020 – Data Structures and Algorithm Design
Examines efficient data structures, algorithm analysis, optimization techniques, recursion, searching, sorting, and computational complexity.
AISE 3030 – Software Engineering Principles
Explores software development methodologies, software lifecycle management, requirements engineering, design patterns, testing, and documentation.
AISE 3040 – Database Systems and Data Engineering
Introduces relational databases, NoSQL databases, data modeling, data pipelines, data warehousing, and data integration for intelligent applications.
AISE 3050 – Machine Learning for Software Engineers
Examines supervised and unsupervised learning, predictive modeling, feature engineering, model evaluation, and AI integration into software systems.
AISE 3060 – Artificial Intelligence Algorithms
Studies search algorithms, knowledge representation, reasoning systems, optimization methods, intelligent agents, and decision-making models.
AISE 3070 – Software Architecture and Design
Focuses on scalable software architecture, microservices, distributed systems, enterprise architecture, and design principles for AI-enabled applications.
AISE 3080 – Cloud Computing and DevOps
Examines cloud infrastructure, continuous integration, continuous deployment, containerization, infrastructure automation, and cloud-native application development.
AISE 3090 – Cybersecurity for AI Systems
Introduces secure software development, identity management, encryption, adversarial machine learning, privacy protection, and risk management.
AISE 3100 – Human-Computer Interaction
Explores user-centered design, usability engineering, accessibility, interface development, and user experience for intelligent systems.
AISE 3110 – Internet of Things and Intelligent Systems
Examines connected devices, embedded systems, sensor networks, edge computing, and AI-enabled IoT applications.
AISE 3120 – Natural Language Processing Applications
Introduces techniques for language understanding, text analytics, conversational AI, language models, and intelligent communication systems.
AISE 3130 – Computer Vision Systems
Explores image processing, object recognition, visual analytics, facial recognition, autonomous vision systems, and industrial AI applications.
AISE 3140 – Systems Analysis and Integration
Develops skills in systems analysis, enterprise integration, workflow automation, interoperability, and systems implementation.
AISE 3150 – Software Quality Assurance and Testing
Examines software testing methodologies, automated testing, quality assurance processes, performance evaluation, and reliability engineering.
AISE 3160 – AI Ethics, Governance, and Compliance
Explores ethical AI development, algorithmic fairness, accountability, transparency, regulatory compliance, and responsible innovation.
AISE 3170 – Agile Project Management for AI Development
Focuses on agile methodologies, Scrum, project planning, team leadership, innovation management, and AI product development.
AISE 3180 – Enterprise AI Applications
Examines the implementation of AI technologies across healthcare, finance, manufacturing, education, logistics, cybersecurity, and smart infrastructure.
AISE 3190 – Capstone Project in AI Software and Systems Engineering
Students design, develop, deploy, and present a comprehensive AI-enabled software system that integrates software engineering principles, intelligent technologies, systems architecture, and ethical considerations.
Career Opportunities
Graduates are prepared for careers in AI software engineering, systems engineering, machine learning, intelligent systems development, cloud AI, data engineering, DevOps, and enterprise software development.
Employment Sectors
Graduates may find employment in software development companies, artificial intelligence and machine learning firms, cloud computing providers, financial technology companies, healthcare technology organizations, manufacturing and industrial automation companies, telecommunications providers, cybersecurity firms, government technology agencies, research laboratories, consulting and digital transformation firms, and technology startups and innovation hubs.
Ready to Build the Next Generation of AI Software?
Gain the technical skills needed to design, develop, and deploy AI-driven software systems. Take the next step toward a career in AI software engineering or graduate study.
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