Overview
In the Industrial Revolution 4.0, in which self-driving cars, assistive robots, and many automatic systems have become a product of the artificial intelligence revolution, which will change the way we live and work, artificial intelligence professions are classified as professions of the future. The Master’s program in Artificial Intelligence provides students with the basic principles of artificial intelligence to enable them to critically evaluate theories, techniques, tools and systems used in interdisciplinary application areas. The student will gain an understanding and practical application of data analysis technology and a range of machine learning models for model building and develop transferable computational and statistical skills for model evaluation. In addition, students will learn about the core components of artificial intelligence systems such as natural language processing, computer vision and robotics, and students will also develop key employability skills such as teamwork, report writing and communication skills.
Goals
- Foundational Knowledge: Equip students with a strong foundational understanding of computer science, mathematics, and engineering principles that underpin the fields of artificial intelligence and robotics.
- Practical Skills: Ensure that students acquire hands-on experience in designing, building, and programming robotic systems, as well as implementing AI algorithms and models.
- Problem-Solving Proficiency: Foster critical thinking and problem-solving skills, enabling students to tackle complex, real-world challenges in AI and robotics with innovative solutions.
- Interdisciplinary Approach: Emphasize the interdisciplinary nature of AI and robotics, encouraging students to integrate knowledge from various domains such as biology, physics, psychology, and social sciences to inform their designs and strategies.
- Ethical Consideration: Instill a strong ethical framework in students, ensuring they understand the societal and ethical implications of AI and robotic systems, and emphasizing the importance of responsible design and deployment.
- Research Orientation: Encourage students to engage in research activities, allowing them to delve deeper into specific areas of interest, stay updated with the latest advancements, and contribute to the evolution of the field.
- Collaboration and Teamwork: Promote collaborative learning and teamwork, preparing students to work effectively in diverse teams and multidisciplinary settings, crucial for large-scale AI and robotics projects.
- Lifelong Learning: Cultivate a mindset of continuous learning, emphasizing the importance of staying updated in a rapidly evolving field, and preparing
