Overview

This is a postgraduate Advanced School (Italian: “Scuola Avanzata, post laurea specialistica”) designed to meet the fast-growing demand of the job market  for new skills and competencies related to advanced fields of Artificial Intelligence (AI) and relevant for the economy, research system, administration, and society.

The School aims to form a new generation of highly specialised professionals and researchers in the innovative fields of AI and Machine Learning (in particular deep neural networks), and of computational modelling of brain, behaviour, and society. These topics do not cover the several topics encompassed by Artificial Intelligence, but are a starting point building on the core competences of the research and professional network supporting the School.

The key distinguishing element of the School is the interdisciplinary investigation and use of artificial and natural intelligence for research and application purposes. This is be based on:

  • 4 months of strongly interdisciplinary courses, 2 days x 8 hours  per week (252 hours in total), related to both technological applications of AI and machine learning and research on brain, behaviour and society 
  • A stimulating environment involving both researchers and professionals from companies
  • A highly motivated interdisciplinary class group 

School main advantages for the Sponsoring Companies and for the Supporting Research Institutes

  • Selection, formation and recruiting of talents: thanks to its hub-role within a rich network of academic and research institutes, the School attracts highly talented postgraduate students and forms them in AI advanced techniques. The students represent a highly valuable asset from which the sponsoring Companies and Research Groups could draw talented personnel with fresh AI expertise.
  • Advanced project carried out together with the Sponsoring Company/Supporting Research Institute: since the first day of the school, the student could work on a project previously identified with the Company or Research Group. This will bring utility to both the Company/Research Group, as the project will address a key problem relevant for them, and for the student, who will work on an important real-life project.
  • Networking and acquisition of know-how on new AI technologies: possibility of joining a network of advance-research and corporate agents  thus accessing competitive advantages rendered by the new AI technologies.

School main features for the students

  • Deep understanding and capacity to apply to real-life problems:
    • Machine learning and deep neural networks techniques, and/or
    • Computational models for understanding reality, in particular brain, mind, and society
  • Basic hands-on machine learning project
  • Acquisition of key soft skills: the School will aim to give to the student not only knowledge and content-related skills, but also soft skills related to project working, flexibility, continuous-learning, problem solving, professionalism, SMART-goal setting, efficient time management, self-coaching, team work.
  • Networking, possibility of starting a high-profile career in AI fields: the close interaction of the students with important high-tech Companies and Research Centers will allow them to start a high-profile career as professionals or as PhD Students/Researchers.

School program tailored on the student

The learning and training path followed by each student will be highly personalised based on her/his project, learning needs, and interests, drawing from the multiple School resources (Fundamentals Courses, Specialistic Courses, Focused Courses; Interdisciplinary student activities; School Mentors/Tutors; School Advisors).

Selection criteria and procedure

Detailed application instructions are available here.

Prerequisites of perspective students, and knowledge acquired with the School

The school is open to students of all university faculties/departments. The philosophy of the School is indeed that variety is an important asset to foster the School interdisciplinary nature and is in line with its long-life learning open perspective. In this respect the School should be intended as a container of resources from which specific resources will be drawn to tailor a specific learning path onto the learning needs and project of the specific student.

For this reason, it is very important that if you are a perspective student you contact us as soon as possible, before the submission, to evaluate together your case and consider possibilities that fit your needs and goals!

Instead, important prerequisites to fully benefit of the School program are a keen motivation, interest on AI, will to learn, desire to interact with and act within an interdisciplinary network.

We have identified three groups of students coming from different university backgrounds and hence having different knowledge and learning needs as follows.

Students from biology/neuroscience, psychology, philosophy, law, economics, political sciences, communication sciences:

  • Knowledge and skills already possessed:
    (1) Extensive knowledge of the contents of a specific topic
  • Knowledge and skills to acquire from the School:
    (2) Capacity to face problems with a quantitative approach and mindset, acquisition of fundamental math and statistics notions needed for machine learning;
    (3) Capacity to program; knowledge and skills on AI approaches and techniques
    (4) Capacity to apply the acquired knowledge and skills to real-life research/application problems

Students from math, physics, chemistry, statistics:

  • Knowledge and skills already possessed:
    (1) Extensive knowledge of the contents of a specific topic;
    (2) Capacity to face problems with a quantitative approach and mindset
  • Knowledge and skills to acquire from the School:
    (3) Capacity to program; complements of math and statistics oriented to machine learning; in-depth understanding and skilled-use of AI approaches and techniques
    (4) Capacity to apply the acquired knowledge and skills to real-life research/application problems

Students from engineering, and computer science:

  • Knowledge and skills already possessed:
    (1) Extensive knowledge of the contents of a specific topic;
    (2) Capacity to face problems with a quantitative approach and mindset
    (3) Capacity to program; possibly some knowledge on AI
  • Knowledge and skills to acquire from the School:
    (3) Complements of math and statistics oriented to machine learning; in-depth understanding and skilled-use of AI approaches and techniques
    (4) Capacity to apply the acquired knowledge and skills to a real-life research/application problems

Additional advantages for students

Students interested in a professional career (in companies or start-ups):

  • Internship involving a project on a company need, carried out within the company with the assistance of the School experts
  • Getting contacts and becoming part a network formed by top-level/advanced-technology research institutes, companies, researchers, and professionals: a fundamental element to build a future professional career in the booming sector of big-data analysis and AI
  • Possibility of final hiring in a company, or to create own start-ups (contacts with start-up incubators/accelerators)

Students interested in a career as researchers:

  • Internship involving a project on state-of-the-art research problem within a top-level research group
  • Getting contacts and becoming part a network formed by top-level/advanced-technology research institutes, companies, researchers, and professionals: a fundamental element to find a PhD in a topic of preference and make the first step to become a researcher
  • Scientific publication(s), the key element to win a national or international PhD enrollment with bursary

Important dates

  • 30 June 2024: Early registration to get fee discount (10%). The 10% discount is also applied in case of selected modules. Discounts cannot be combined. Those already benefiting from either the 30% or 40% discount are ineligible to receive the early registration discount as well.
  • 25 September 2024: Deadline for submission of student applications (contact the School administration for applications beyond this deadline)
  • 28 September 2024:
    • Communication of outcome of students’ Selection 1
    • Start of students enrollment
  • Before 1 October 2024: Payment of first part of the fee (2300 € for full school).
  • Early October 2024: School start
  • Before 15 January 2025: Payment of remaining part of the fee
  • Early March 2025:
    • End of Courses
    • Certificate for students after developing and hands.on Basic Machine Learning Project
    • For selected students
      • Examination for passing to Internship phase
      • Start of Internship for Company and Research Internship Program students
  • April-October 2025: End of Internship and Certificate for Company and Research Internship Program students

Fee, scholarships, internship

  • Full School fee: 4600 € (a 40% discount for university students and unemployed)
  • All the AS-AI student could also select specific modules, paying just for that (see here), with a possible 10% discount in case of early registration
  • On-going scholarship for students available
  • The School enrollment will give the right, and require, to become members (“socio”) for free of the Association “Associazione culturale science2mind”.
  • CNR staff benefit from a 30% discount on the enrollment fee.
  • The price is VAT included

Final School Certificate

The final “Certificate: Advanced School in AI” will specify the successful attendance of the School. Moreover, the Certificate will specify the Courses successfully attended (title and duration), Project title, and Internship (when present). The Certificate will be signed by the AS-AI Director Daniele Caligiore and by the AS-AI President Gianluca Baldassarre.