The Master program in Computer Engineering program offers a specialized track in Applied Artificial Intelligence (AI) focusing on advanced concepts and techniques within this dynamic field. This program is designed for individuals with a robust background in computer science and engineering, mathematics, or related domains, aiming to specialize in the intricate theory and practical application of AI and machine learning technologies.
The curriculum of the M.Sc. in Applied AI encompasses a blend of core courses, elective courses, and a research project or thesis component. Core courses and elective courses delve into the following subjects and applications, among others:
- Machine Learning Algorithms: A comprehensive exploration of diverse machine learning algorithms, encompassing supervised, unsupervised, and reinforcement learning.
- Neural Networks and Deep Learning: In-depth study of the architecture and training of deep neural networks, with applications ranging from image recognition to natural language processing.
- Data Mining and Pattern Recognition: Techniques for extracting significant patterns and insights from extensive datasets.
- Natural Language Processing (NLP): The amalgamation of AI and linguistics to comprehend and process human language.
- Computer Vision: Fundamental concepts associated with enabling computers to interpret visual information, including object recognition and image analysis.
- Machine learning for biomedical signal and image analysis: Explore the intricacies of extracting valuable information from complex biomedical data by applying noise reduction techniques and implementing feature extraction methods. In addition, several AI techniques will be explored to enhance image analysis, automate disease detection, and aid in the interpretation of medical images such as MRIs, CT scans, and X-rays.
- Machine learning for health care: Explore the integration of machine learning techniques to predict diseases, assist in diagnosis, and personalize treatment plans. This includes developing AI models that learn from data and make informed decisions in a medical context.
- Cloud for AI and Big Data Analysis.
- Robotics Programming.
To explore the study plan of the Thesis Track, please refer to the following link:
For insights into the study plan of the Comprehensive Track, please refer to the following link:
Comprehensive track study plan