Since September 2015, UCA 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, UCA will also run an entry point in Emotion Artificial Intelligence (EMAI) supported by the EU project EMAI4EU. The exit point in EMAI will open in September 2026; it will offer 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. Some details are given at the end of this page.
Be aware of the great opportunity by studying as an ENTRY student at UCA => you will be registered to two UCA degrees, mainly the UCA Polytech Nice Sophia engineering degree in Sciences Informatiques (Computer science), and the Master in computer science of UCA. The engineering degree is well-recognized through two labels: by the French CTI and the European EUR@ACE, still it requires you to commit to extra requirements, especially a French proficiency level at least A2 at the end of (or at worst 2 years after) your studies as an UCA engineering student (you may only graduate with the Master degree at the end, if some requirements get not fulfilled).
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 UCA 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, some of them highly recommended given the track (see *) given timeschedule permits it
- Innovation and Entrepreneurship courses: I&E (24 ECTS).
Data science and Emotion A.I 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 (2024-2025, subject to slight modifications for 2025-2026)
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 |
| Computer networks |
| Evolving Internet |
| Middleware and Service Oriented Computing |
| Data Science (*) |
| Deep Learning (*) |
| A.I. Game programming |
| A.I. Engineering |
| Text mining and NLP |
| Machine learning for image analysis |
| Introduction to Security |
| Blockchain & privacy |
| Security and privacy 3.0 |
| R&D project |
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 and Machine Learning | 3 |
| Five Elective courses (for a total of 9 ECTS) |
|---|
| Embedded A.I., sensors and actuators |
| Ethics of Data (*) |
| NLP (*) |
| Combinatorial optimization |
| Operational research |
| Graphs algorithms |
| Advanced computer networks |
| Distributed big data |
| R&D project |
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 mid of June) | 0,35 |
| I&E for venture creation / Summer school : globally organized by EIT Digital, July-August | 0,25 |
Emotion Artificial Intelligence entry program (from 2025-2026) (draft version)
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 |
| Computer networks |
| Evolving Internet |
| Middleware and Service Oriented Computing |
| Data Science |
| Advanced tools in maths & stats (*) |
| A.I. Game programming |
| A.I. Engineering |
| Text mining and NLP |
| Machine learning for image analysis |
| Logic for AI |
| Problem solving (*) |
| Introduction to Constraints programming |
| Introduction to Security |
| Blockchain & privacy |
| Security and privacy 3.0 |
| Information visualisation |
| R&D project |
Innovation & Entrepreneurship Courses: same as for the DSC track
Semester 2
Technical Courses
| Compulsory courses (6 ECTS) | Number of ECTS |
|---|---|
| NLP | 3 |
| Computer vision and Machine Learning | 3 |
| Five Elective courses (for a total of 9 ECTS) |
|---|
| Embedded A.I., sensors and actuators (*) |
| Ethics of data (*) |
| Anthropology and Ethics of Technics |
| Advanced logic |
| Combinatorial optimization |
| Operational research |
| Graphs algorithms |
| Advanced computer networks |
| Distributed big data |
| Parallelism |
| Creating interactive virtual worlds |
| Web |
| R&D project |
Innovation & Entrepreneurship Courses: same as for the DSC track
Emotion Artificial Intelligence exit program (from 2026-2027) (prospective program version)
The program is organized the same as the Data Science exit track, into
- One compulsory courses block -6 ECTS- holding 3 courses
- One elective courses block -12 ECTS- holding 6 courses
- One Research & Development project -6 ECTS-, in group or individual
- The I&E Study mandatory course -6 ECTS.
AI and Computer Science:
| Advanced Data Mining |
| Advanced topics in deep learning |
| Applied A.I. |
| Artificial intelligence engineering |
| Machine learning for Image analysis |
| Reinforcement learning |
| Virtual Reality |
Emotion AI specialization:
| Decision theory |
| AI and emotions |
| Multimodal emotion recognition from video and biosignals |
| Emotion and decision-making process |
| Behavioural economics and emotions |
| Discourse dialog modelling |
| Spiking Neural Networks |