About the program
The Bachelor of Artificial Intelligence is a modern program that responds to the rapid transformation of intelligent computing. It combines computer science, mathematics and algorithms with practical applications that enable machines to “think” and make decisions.
It prepares technical professionals able to design and develop intelligent systems that interact with their environment and analyze data. The program develops analytical thinking, programming skills and an understanding of the mathematics behind AI technologies such as machine learning, computer vision and natural language processing.
Graduates are prepared to work in advanced fields including industry, health, transport, education and the everyday digital applications that increasingly rely on intelligent systems.
Program outcomes
- Demonstrate a thorough understanding of core AI concepts such as algorithms, machine and deep learning, natural language processing and computer vision, together with the mathematical and statistical principles behind them.
- Recognize the ethical, legal and social dimensions of AI applications, and handle them responsibly and with professional awareness.
- Analyze complex problems and design effective solutions using the right AI techniques, evaluating models for efficiency, accuracy and interpretability.
- Apply critical, methodical thinking to developing and testing intelligent models, and choose the most suitable one for the context.
- Design and develop intelligent applications with common AI tools such as Python, TensorFlow and Scikit-learn, and carry out applied projects that use data and intelligent modeling to solve real-world problems in a range of fields.
- Work effectively in multidisciplinary teams, communicate technically with professionalism, uphold professional ethics, and keep learning independently to keep pace with this fast-moving field.
Study plan
The approved plan in the university system, by semester.
1Semester 14 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| CS104 | Programming Fundamentals (Python / Java) | 3 | — |
| CS102 | Introduction to Computer Networks | 3 | — |
| ST101 | Calculus and Linear Algebra | 3 | — |
| EN101 | English Language 1 | 3 | — |
2Semester 24 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| EN102 | English Language 2 | 3 | English Language 1 |
| CS106 | Algorithms and Data Structures | 3 | — |
| AI103 | Introduction to Artificial Intelligence | 3 | — |
| ST105 | Probability and Statistics | 3 | — |
3Semester 34 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| CS107 | Software, Mobile and Web Application Development | 3 | Algorithms and Data Structures |
| DS207 | Data Science | 3 | — |
| AI201 | Deep Learning and Neural Networks | 3 | Introduction to Artificial Intelligence |
| AI211 | Machine Learning | 3 | Probability and Statistics |
4Semester 44 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| DS206 | Big Data | 3 | Data Science |
| CS208 | Databases | 3 | Algorithms and Data Structures |
| AI203 | Computer Vision | 3 | Machine Learning |
| AI209 | Natural Language Processing | 3 | Machine Learning |
5Semester 54 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| AI204 | AI Prompt Engineering | 3 | Introduction to Artificial Intelligence |
| AI205 | Generative AI | 3 | Deep Learning and Neural Networks |
| AI210 | Robotics | 3 | Computer Vision |
| AI202 | AI Product Design | 3 | Software, Mobile and Web Application Development |
6Semester 64 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| AI212 | Large Language Model Engineering | 3 | Generative AI |
| AI401 | E-Commerce | 3 | Software, Mobile and Web Application Development |
| AI402 | Technology Project Management | 3 | Software, Mobile and Web Application Development |
| AI403 | Digital Humanities | 3 | English Language 2 |
7Semester 74 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| AI404 | Philosophy in the Age of AI | 3 | Introduction to Artificial Intelligence |
| AI405 | Harnessing AI for Research | 3 | Generative AI |
| AI406 | AI and Financial Technology | 3 | Data Science |
| AI407 | Smart Supply Chains | 3 | Big Data |
8Semester 84 courses · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| AI408 | AI Applications in Cybersecurity | 3 | Generative AI |
| AI409 | AI and Public Policy | 3 | Philosophy in the Age of AI |
| AI410 | AI and Sport | 3 | Introduction to Artificial Intelligence |
| AI213 | Applied Research in Artificial Intelligence | 3 | Generative AI |
9Semester 91 course · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| PR302 | Internship | 12 | — |
10Semester 101 course · 12 credit hours
| Code | Course | Hours | Prerequisite |
|---|
| PR301 | Graduation Project | 12 | — |
Career paths
