School Structure and Organization
Students are offered FUNDAMENTAL COURSES, SPECIALISTIC COURSES, FOCUSSED COURSES, seminars and activities, with the aim to provide both a deep knowledge and specialisation and a broad view and transversal competences, skills and perspectives. The student can select among different COURSES to build the personalized learning and training path based on her/his project, learning needs, and interests with the support of the School President, Director and of School Advisors. Alternatively, the student can select one of the three learning and training paths (Tracks) proposed by the School.
The need for a high specialisation of the student is attained through the organization of the School along 3 different Tracks:
- Track 1: Machine Learning Applications (MLA)
- Track 2: Computational Embodied Neuroscience (CEN)
- Track 3: Computational Social Science (CSS)
Each Track involves initial general FUNDAMENTAL COURSES, to join a common scientific background filling in possible University knowledge gaps, plus a number of SPECIALISTIC COURSES, depending on the selected track. The curriculum is completed by a range of short FOCUSED COURSES, to widen the perspective on the individual Project, and activities designed to support the acquisition of cross-field knowledge and personal capabilities.
According to the different needs of students, companies, future professionals and researchers, the School offers three possible training programs, as detailed below.
All the Tracks and all the Learning programs have one single cornerstone: from the very beginning, the work on a project with a SMART goal. The project work is the pivot of each student formation. Once assigned a project (both for the upskilling program, and for the company and research internship programs), the School is designed to offer the student a number of resources from which actively drawing to carry it out with success.
Upskilling Learning Program – New Skills for Industry 4.0 or research
The Upskilling Learning Program (4 months, 2 days/week, 288 h on Courses, 128 h on Mini Project off-room) requires a part time frequency of two days per week for 4 months and is focused on the management of an individual project. The project is the pivot of each student formation. It is identified on the basis of the interests and attitude of the students, or on a portfolio of possibilities offered by the companies/research groups joining the School network.
The Upskilling Learning Program has been designed for the acquisition of a deep know-how on a specific field and approach, with all the theoretical and practical skills needed to build, or upskill, in case, a new professional career in ICT. Students will also acquire soft skills, in particular, project-based working, continuous-learning capabilities, problems solving, and flexibility.
The Upskilling Learning program aims to give a high professional profile founded on specific knowledge and skills in a particular application area and to introduce the student into a network of people and organisations: the latter is a fundamental means to seek a future profession in a high-tech application field.
Students will earn the Advanced School Course Diploma, with laude in the case of particular success and achievement on the project.
Company Internship Program – Build real-world machine learning solutions
The Company Internship Program (4 months, 2 days/week, 288 h on Courses, 128 h on Project off-room + INTERNSHIP), similarly to the Upskilling Learning Program, requires a part time frequency of two days per week for 4 months, but it is more strongly company-oriented, including, at the end of the courses, a period of internship in a Company joining the network of the School. Wage, bursary and duration will be defined individually according to the availabilities.
The Company Internship Program aims to select talented graduate students (BA/MA) to develop the case-specific needed skills and use them to deploy the most advanced AI tools and strategies for the solution of real-life challenging problems, with the high-level support of interdisciplinary teams of researchers and senior professionals.
The Program, on the base of Companies’ specific interests, can include a system of economic incentives to reward the students’ talent and commitment in contributing to reaching the target of the project.
If you are interested in an internship in a Company that hasn’t yet participated in the School, you must let us know in advance of contacting them so that we can get them involved in the program.
The admission to this program can be based on the selection of a proposal submitted by the interested students on company challenges. Before starting the internship, the program includes a mid-school check-point (Selection 2), as a guarantee of excellence to reward the Company’s commitment. In the case of a negative evaluation, the student will earn the Company Learning Program Diploma.
Research internship program – Start a career in research
The Intensive Learning Program (4 months, 2 days/week, 1 year, 288 h on Courses, 375 h on Research Project Start + 8 months, 2 days/week, Internship and Project finalization in Research Lab) requires, finally, a full time frequency of five days per week for 1 year. It has been designed for students oriented towards a research career in the scientific study of brain, behavior and society with computational models linked to psychology and neuroscience and for those interested in artificial intelligence, in particular machine learning applied to autonomous learning robots.
The collaborative research programs will be carried out within high-level Research Groups operating in the fields of interest of the School, in particular, the LOCEN and LABSS laboratories of the ISTC/CNR, actively contributing to the curriculum.
The program aims at furnishing deep knowledge and skills on specific topics and techniques and also to gain one or more scientific publications: the latter ones are a fundamental means to continue to do research as a profession, for example, to seek a funded PhD in Italy or abroad.
The admission to the program depends on a selection based on keen interest in the topics, potential and forma-mentis able to frame brain and behaviour issues in a quantitative and computational form so as to face them with computational models.