Data Science Entry and AI with Affective Computing Entry programs

 
Since September 2015, UniCA runs an entry point in Data Science (DSC). The exit point in DSC is running since 2016, it offers a specialization entitled Multimedia and Web Science for Big Data.
From September 2025, UniCA also runs an entry point in A.I with Affective Computing (Emotion AI) supported by the EU-funded project EMAI4EU. The exit point in AIAC opens in September 2026; it offers a specialization entitled  "Holistic interdisciplinary aspects" whose goal is to deeper understand the multifaceted domain of emotions, from signal processing and machine learning dimensions of emotion capture, to psychological, behavioral, societal, and ethical aspects. 

As for all tracks that UniCA hosts, that pertain to the EIT Digital Master school, the students will receive an "EIT label" certificate, which aims at attesting the Innovation & Entrepreneurship skills gained during the programme.
Be aware of the great opportunity by studying as an ENTRY student at UniCA => you get registered to the UniCA Polytech Nice Sophia engineering degree in Sciences Informatiques (Computer science). This engineering degree is well-recognized through two labels: by the French CTI and the European EUR@ACE, still it requires you to commit to an extra requirement: a French proficiency level at least A2 at the end of (or at worst 2 years after) your studies as an UCA engineering student (during the entry year, French classes are proposed to non French speaking students ; while French speaking students have to enroll to another language class).
 

 

These entry tracks are organized in two semesters during which you can obtain (at least) 60 ECTS (European Credits Transfer System), divided into:

  • 36 ECTS in technical courses
  • 24 ECTS in Innovation and Entrepreneurship (I&E). This is achieved by attending: the corresponding courses offered at UniCA in I&E (see below) and the Summer School  organized by the EIT Digital Master school, at the end of the academic year.

Each student should acquire at least 60 ECTS during the first year of its chosen entry track. The lectures and ECTS are distributed as follows:

  • Technical courses for a total of 36 ECTS, distributed in blocks of courses, each block providing ECTS. Split as compulsory courses in one block per semester, plus a set of elective courses in another block, some of them highly recommended given the track (see *) given timeschedule permits it
  • Innovation and Entrepreneurship courses: I&E (24 ECTS).

Data science and A.I. with Affective Computing tracks entry programs will mostly differ in the Compulsory courses of each semester. And the guidance that will be provided to students to choose elective courses appropriate for their track.

Data Science  entry program (2026-2027)

Semester 1 

Technical Courses

Compulsory courses (6 ECTS) Number of ECTS
Methods for Optimization and Machine Learning 3
Advanced tools in Maths and stats 3
Five Elective courses (for a total of 15 ECTS, each worths 3)
Big Data technologies (*)
An algorithmic approach of distributed systems
Large scale distributed systems
Virtualized cloud infrastructures
Evolving Internet
Middleware and Service Oriented Computing/ Project S7
Distributed computing and learning
Data Science (*)
Deep Learning (*)
A.I. Game programming
A.I. Engineering
Text mining and NLP
Machine learning for image analysis
Machine learning: theory and algorithms
Introduction to Security
Blockchain & privacy
Vie privée et sécurité (in French)
Web
R&D project in DSC

Innovation & Entrepreneurship Courses

I&E Semester 1 (9 ECTS) Coefficient
Basics in I&E  0.3
Business Dev. Lab Part 1 0.3
Business Intelligence 1 0.3
Foreign language 0.1

Semester 2

Technical Courses

Compulsory courses (6 ECTS) Number of ECTS
Data valorization 3
Computer vision 3
Three Elective courses (for a total of 9 ECTS)
Embedded A.I., sensors and actuators
Ethics of Data (*)
NLP (*)
Combinatorial Optimization
Data science for complex networks
Scalable Data science
R&D project DSC

Innovation & Entrepreneurship Courses

I&E Semester 2 (15  ECTS) Coefficient
Business Intelligence 2: Marketing & Consumer Experience 0,15
I&E complementary course: Commercialisation Strategy 0,15
Foreign language 0,1
Business Dev. Lab 2  (spread in the empty slots, from early march till end of April/mid of May maximum) 0,35
I&E for venture creation / Summer school : globally organized by EIT Digital, in general in July  0,25

Artificial Intelligence with Affective Computing entry program (2026-2027) 

 

Semester 1 

Technical Courses

Compulsory courses (6 ECTS) Number of ECTS
Methods for Optimization and Machine Learning 3
Deep Learning 3
Five Elective courses (for a total of 15 ECTS, each worths 3)
Big Data technologies (*)
An algorithmic approach of distributed systems
Large scale distributed systems
Virtualized cloud infrastructures
Evolving Internet
Middleware and Service Oriented Computing/Project S7
Distributed computing and learning
Data Science
Advanced tools in maths & stats (*)
A.I. Game programming 
A.I. Engineering (*)
Text mining and NLP
Machine learning for image analysis
Machine Learning: Theory & algorithms 
Problem solving (*)
Web
Introduction to Security
Blockchain & privacy
Vie privée et Sécurité (in French)
Information visualisation  
R&D project in AIAC

Innovation & Entrepreneurship Courses: same as for the DSC track

Semester 2

Technical Courses

Compulsory courses (6 ECTS) Number of ECTS
NLP 3
Computer vision 3
Three Elective courses (for a total of 9 ECTS)
Embedded A.I., sensors and actuators (*)
Ethics of data (*)
Anthropology and Ethics of Technics
Logic for A.I. (*)
Combinatorial Optimization
Scalable Data Science
Parallelism
Creating interactive virtual worlds
R&D project in AIAC

Innovation & Entrepreneurship Courses: same as for the DSC track