Students are expected to acquire: knowledge of advanced machine learning models for structured data processing knowledge of recurrent/recursive neural networks knowledge of probabilistic (generative) learning models, with particular focus on timeseries and structured data processing knowledge on relevant applications of machine learning models some knowledge of state-of-the-art research on machine learning

During the oral exam the student must be able to demonstrate his/her knowledge of the course material and be able to discuss the reading matter thoughtfully and with propriety of expression. With the oral presentation (to be made to the teacher and the other students) or the written essay, the student must demonstrate the ability to approach a circumscribed research problem, and organise an effective exposition of the results.

Methods:

• Final oral exam
• Final essay
• Final laboratory practical demonstration
• Oral report