The Master of Science in Artificial Intelligence is a two-year, full-time postgraduate program designed to meet European standards and the Bologna Process requirements. The program comprises 120 ECTS credits, blending core AI theory, advanced technical skills, research, ethics, and practical experience. The curriculum is aligned for joint or dual-degree collaboration with European partner universities.

Program Structure

Detailed Module Breakdown

Semester 1: Core Foundations (30 ECTS)

o   Mathematics for AI (Linear Algebra, Probability, Statistics) – 6 ECTS

o   Introduction to Artificial Intelligence – 6 ECTS

o   Programming for Data Science and AI (Python, R) – 6 ECTS

o   Data Structures and Algorithms – 6 ECTS

o   Research Methods and Academic Writing – 6 ECTS

Semester 2: Advanced AI Topics (30 ECTS)

o   Machine Learning – 6 ECTS

o   Deep Learning – 6 ECTS

o   Natural Language Processing – 6 ECTS

o   Computer Vision – 6 ECTS

o   Ethics, Law, and Social Implications of AI – 6 ECTS

Semester 3: Electives & Mobility (30 ECTS)

o   Students select electives from a list (e.g., Robotics, AI in Healthcare, Reinforcement Learning, Big Data Analytics, Human-Centered AI) – 18 ECTS

o   Mobility Option: Exchange semester at a European partner university (modules recognized for credit) – up to 18 ECTS

o   Interdisciplinary Project or Seminar – 6 ECTS

o   Entrepreneurship and Innovation in AI – 6 ECTS

Semester 4: Thesis & Internship (30 ECTS)

o   Master’s Thesis (original research or applied project) – 24 ECTS

o   Professional Internship or Industry Placement – 6 ECTS

Learning Outcomes

o   Demonstrate advanced knowledge of AI theory, algorithms, and applications

o   Apply machine learning and deep learning techniques in practical scenarios

o   Critically assess ethical, legal, and societal implications of AI

o   Conduct independent research and communicate results effectively

o   Collaborate in multidisciplinary and international teams

Admission Requirements

o   Bachelor’s degree in Computer Science, Engineering, Mathematics, or related discipline

o   Proof of English proficiency (IELTS/TOEFL) as per European standards

o   Motivation letter and academic references

Quality Assurance & European Standards

The program structure follows the European Qualifications Framework (EQF) Level 7 and the Bologna Process guidelines for master’s degrees. Assessment methods include coursework, exams, projects, and thesis defense. Mobility and recognition of credits are facilitated via ECTS and collaboration agreements with partner universities.

Conclusion

This MS in Artificial Intelligence program enables Innoversity to offer a rigorous, internationally recognized postgraduate degree, preparing graduates for careers in academia, industry, and research across Europe and beyond.

Upon successful completion of the MS in Artificial Intelligence, graduates will be able to:

1. Demonstrate advanced knowledge of artificial intelligence theories, algorithms, and methodologies.
2. Design, develop, and implement intelligent systems capable of solving complex real-world problems.
3. Apply machine learning and deep learning techniques to build predictive and intelligent applications.
4. Develop AI-powered solutions using neural networks, reinforcement learning, and advanced computational models.
5. Utilize natural language processing (NLP) techniques for language understanding, text analytics, and conversational AI systems.
6. Apply computer vision technologies for image recognition, object detection, and intelligent visual systems.
7. Analyze and process large-scale datasets to support AI-driven decision-making.
8. Evaluate and optimize AI models using appropriate performance metrics and validation techniques.
9. Design ethical, transparent, and responsible AI systems while addressing fairness, privacy, and governance concerns.
10. Apply AI technologies in domains such as healthcare, finance, education, cybersecurity, manufacturing, and smart cities.
11. Conduct independent research and innovation in emerging areas of artificial intelligence.
12. Communicate technical concepts and AI solutions effectively to technical and non-technical audiences.
13. Collaborate in multidisciplinary teams to develop and deploy intelligent technologies.
14. Assess emerging trends and advancements in artificial intelligence and related technologies.
15. Contribute to digital transformation and innovation initiatives through AI-driven solutions and strategic leadership.