About the program
The Master of Artificial Intelligence, with its focus on computer vision, is an advanced learning experience that prepares students to develop intelligent systems able to “see” and understand images and video in a way that mimics human perception.
This specialization is one of the cornerstones of artificial intelligence and is widely used in applications such as facial recognition, medical image analysis and smart surveillance.
The program rests on a strong scientific foundation in machine learning, offering in-depth academic content on AI and machine learning models and techniques, together with practical experience that reflects the real needs of the job market.
Program outcomes
- Apply core and advanced concepts of AI and machine learning, with a special focus on computer vision, to understand and develop systems that analyze and process images and video effectively.
- Analyze complex problems in AI and design technical solutions based on machine learning models, taking into account the ethical and social aspects of AI use.
- Use modern AI tools and technologies such as TensorFlow, PyTorch, OpenAI and Microsoft Azure AI to design and deliver real-world applications in areas such as facial recognition, autonomous driving and healthcare.
- Evaluate and interpret the results of intelligent models and algorithms through methodical approaches and rigorous statistical analysis, supporting sound decisions in technical and research settings.
- Generate new knowledge through applied research in AI and computer vision, upholding the highest standards of academic integrity and research professionalism.
- Work effectively in multidisciplinary teams, present technical ideas and proposals with strong communication skills, and pursue continuous professional development in a fast-changing, fast-growing field.
Study plan
The approved plan in the university system, by semester.
1Semester 1
| Code | Course | Hours | Prerequisite |
|---|---|---|---|
| UNI201 | Principles of Statistics | 3 | — |
| UNI102 | Research Methodology | 3 | — |
| AI502 | Advanced Artificial Intelligence | 3 | — |
2Semester 2
| Code | Course | Hours | Prerequisite |
|---|---|---|---|
| UNI103 | Academic Writing and Research Skills | 3 | — |
| UNI105 | Using Artificial Intelligence in the Discipline | 3 | — |
| AI505 | Intelligent Algorithms and Optimization | 3 | — |
3Semester 3
| Code | Course | Hours | Prerequisite |
|---|---|---|---|
| AI503 | Advanced Machine Learning | 3 | — |
| UNI104 | Research Issues | 3 | — |
| AI604 | AI Ethics and Social Responsibility | 3 | — |
4Semester 4
| Code | Course | Hours | Prerequisite |
|---|---|---|---|
| AI504 | Data Engineering and Intelligent Analytics | 3 | — |
| AI509 | Completing the thesis for its defense after the fourth semester | 6 | — |