Second cycle degree in COMPUTER SCIENCE

Campus: PADOVA

Language: English

Teaching period: Second Semester


Number of ECTS credits allocated: 6

Prerequisites: The student should have basic knowledge of programming and algorithms. It is also advisable to be familiar with basic concepts in probability and analysis of multivariate functions.
Examination methods: The student is expected to develop, in agreement with the teacher, a small applicative project. In addition, the student must submit a written report on the project, addressing in a critical fashion all the issues dealt with during its realization. The student will present and discuss the project and, if deemed necessary by the teacher, pass an oral examination.
Course unit contents: The course will cover the topics listed below:
- Introduction:
From human cognition to smart cognitive services; brief intro to AI and ML paradigms.
- Cognitive Services:
Basic concepts; Language, Speech, and Vision Services; major services and API (IBM Watson, Microsoft, Google Cloud); enabling technologies.
- Machine Learning and Application Issues:
Classification; Representation learning and selection of categorical variables; Training and testing; Evaluation measures.
- Visual Recognition:
“Teaching computers to see”: extract rich information from visual data; Challenges: why is computer vision hard?; Designing effective visual features; Representation learning in computer vision; Image understanding.
- Hands-on Practicals:
What’s in the box? How to build a visual recognition pipeline; Using cognitive services for image recognition/understanding; Combining different services in a multi-modal scenario.