DSC Program
Program for EIT Digital Master 2 DSC track
The DSC track consists of two semesters and allows you to earn 60 ECTS (European Credits Transfer System).
The first semester consists of core and elective courses. In addition, each student must complete a Personal Research and Development Project in either one of the local partner institutions (CNRS I3S, CNRS LEAT, CNRS LJAD or INRIA), or by our industrial partners (Orange Labs, SAP research labs, Amadeus, ..., or by the Sophia-Antipolis SMEs ecosystem) for a total of 6 ECTS credits. Subjects are proposed to students during October, so that the project can also start early: approx 1 day per week, plus a four weeks almost full-time period (between Period 1 and 2; End of february: oral defense, delivery of an intermediate report before Christmas, and one final report at the end of semester 1) should be allocated to the project development.
Version from 2019-2020
The slight difference with previous versions is on the list of the mandatory courses for 6 ECTS, and the list of electives to choose from for 12 ECTS (in practice for 6 + 6, in two blocks that can compensate each other).In the block of mandatory courses of 6 ECTS:
- Compression, analysis and visualization of multimedia content course is replaced by the Data Science course (IBM, Amadeus taught course, CECAZ on Big Data and Analytics, and some Jupyter notebook for Kaggle labs/projects, Multimedia based usecases)
- Analysis and indexation of images and videos in big data systems (from shallow to deep learning) course is replaced by a reworked content of Management of massive data (streaming technologies, for multimedia data mainly).
Consequently, in the courses lists below, the needed switches have been applied, but a student can take at the end same list of courses as former exit point students !
Precise time schedule will be gradually published, at edt.polytech.unice.fr/1/invite, in Promotions/Emploi du Temps/Année, choose Master 2 DSC EIT Digital then click week per week to see slots and rooms. All courses except in Valrose Sciences faculty campus are in the Campus SophiaTech, Polytech Nice Sophia (PNS) buildings (Est E, or Ouest O buildings). A welcome day organized by the Graduate school DS4H you belong to is scheduled on Sept. 13th whole day on campus + extra evening event in Nice. An other welcome meeting specific to EIT Digital is also going to be scheduled. An informal meeting with the head of the master is happpening the Sept 4th afternoon at Polytech E+133 at 2pm for those that start the refresher in Maths/Stats course on the next day; a second one can be scheduled if needed later the next week on the Wednesday 11 of sept. Some general level information pertaining to the Polytech Engineering school can be consulted here.
Christmas break starts the Friday 20th of december 2019 after courses if any, and the semester resumes on the Monday 6th of January 2020. If possible, we try not to put you exams on these Friday and Monday, and if possible, also no course. But we cannot garantee that. These two weeks of holidays are the only one you can expect during the 3rd semester. The internship can start from 9th of March 2020, but, as you have to find a position for 4,5 to 6 months and oral defenses happen early September 2020, you can schedule some holidays before, during or after the internship.
Precise time schedule will be gradually published, at edt.polytech.unice.fr/1/invite, in Promotions/Emploi du Temps/Année, choose Master 2 DSC EIT Digital then click week per week to see slots and rooms. All courses except in Valrose Sciences faculty campus are in the Campus SophiaTech, Polytech Nice Sophia (PNS) buildings (Est E, or Ouest O buildings). A welcome day organized by the Graduate school DS4H you belong to is scheduled on Sept. 13th whole day on campus + extra evening event in Nice. An other welcome meeting specific to EIT Digital is also going to be scheduled. An informal meeting with the head of the master is happpening the Sept 4th afternoon at Polytech E+133 at 2pm for those that start the refresher in Maths/Stats course on the next day; a second one can be scheduled if needed later the next week on the Wednesday 11 of sept. Some general level information pertaining to the Polytech Engineering school can be consulted here.
Christmas break starts the Friday 20th of december 2019 after courses if any, and the semester resumes on the Monday 6th of January 2020. If possible, we try not to put you exams on these Friday and Monday, and if possible, also no course. But we cannot garantee that. These two weeks of holidays are the only one you can expect during the 3rd semester. The internship can start from 9th of March 2020, but, as you have to find a position for 4,5 to 6 months and oral defenses happen early September 2020, you can schedule some holidays before, during or after the internship.
Semester 1, October-February (30 ECTS)
Mandatory as elective courses are in general split in two periods (quarters of consecutive 8 weeks including last one for the written exam; first quarter starts at Polytech, the Monday 16/09/19, second starts after the --only-- two weeks of vacation for Christmas break). If not indicated "In French", courses are taught either by default in English, or, on demand if needed.
Mandatory courses (6 ECTS)
The list of mandatory courses from the 2019-20 academic period is such that it is as close as possible to the Data Science - Science des Données (SD) - track of the Master 2 Ingénierie / 5th year of study SD of the applied mathematics and computer science departments of Polytech Nice-Sophia Antipolis engineering school. Mandatory courses constitutes a single module (majeure) of 6 ECTS (within which all course marks are averaged and if it is reaching an overall mark of 10 / 20, then the ECTS are gained).| Period 1 Mandatory courses 2019-20; Majeure SD | Schedule | |
|---|---|---|
| Panorama of Big Data technologies | Monday morning | Coefficient 2 |
| Data Science: industrial seminars (IBM, Amadeus taught course, CECAZ on Big Data and Analytics, and some Jupyter notebook for Kaggle labs/projects) | Friday afternoon | Coefficient 2 |
| Period 2 Mandatory courses 2019-20 | Schedule | |
|---|---|---|
| Management of massive data (mostly network streaming technologies) | Friday morning | Coefficient 2 |
Project Fin d'Etudes (6 ECTS)
| Project Fin d'Etudes | Schedule | |
|---|---|---|
| Personal research and/or development project in Data Science (examples of subjects, SD/Web sections) | Starts october till end of februrary, 4 weeks full time mid nov till mid december | 6 ECTS |
Elective courses (6+6 ECTS)
(pieces of text in yellow have now almost final schedule. @28/8/2019)
| Elective courses list from 2019-20 | Topic | Schedule | Coeff |
|---|---|---|---|
| Statistical machine learning (see p2) (Period1) | Data modeling and analysis | Thursday afternoon, 1:30 pm to 4:30 from 12/09/19 till 5/12/2019 except the Thursdays 19/09/2019, 31/10/2019 , 14/11/2019, 21/11/2019, where course happens the morning at 10am (10 lessons+ last session is exam), Sciences faculty campus NICE, Valrose | 2+2 |
| Statistical computational methods = CART and random forests for high-dimensional data (see p3) (Period 1 and 2) | Data modeling and analysis | Thursday afternoon 1:30 pm,to 4:30 from 31/10/19 till 06/02/2020 (10 lessons+ last session is exam session) except the 7/11/2019 , Sciences faculty campus NICE, Valrose | 2+2 |
| Fouille de données (Period 2) (basic data mining) | Data modeling and analysis | Period 2, Tuesday morning | 2 |
| Compression, analysis and visualization of multimedia content (update in progress with more Deep L) (Period 1) | Data modeling and analysis | Period 1, Monday afternoon | 2 |
| Distributed optimization and games (Period 2) | Data modeling and analysis | Period 2, Wednesday morning | 2 |
| Graph algorithms and optimization (Period 1) | Data modeling and analysis | Period 1, Monday afternoon | 2 |
| Analysis and indexation of images and videos in big data systems (from shallow to deep learning) (Period 2) | Application of data science, in particular on multimedia content and data on the web | Period 2, Wednesday morning | 2 |
| Data mining for networks (Period 2) | Application of data science, in particular on multimedia content and data on the web | Period 2, Thursday afternoon | 2 |
| Web of Data (Period 1), also online as Coursera EIT Digital course | Application of data science, in particular on multimedia content and data on the web | Period 1, Tuesday morning | 2 |
| Semantic Web (Period 2) | Application of data science, in particular on multimedia content and data on the web | Period 2, Tuesday afternoon (prerequisite: web of data) | 2 |
| Security and privacy 3.0 (Period 2) | Data processing supporting technologies | Period 2, Wednesday afternoon | 2 |
| Sécurité des applications web (Period 1, in French) | Application of data science, in particular on multimedia content and data on the web | Period 1, Thursday morning | 2 |
| Blockhain and privacy (Period 2) | Data processing supporting technologies | Period 2, Thursday morning | 2 |
| Peer to Peer (Period 1) | Data processing supporting technologies | Period 1, Tuesday morning | 2 |
| Virtualized infrastructure in cloud computing (Period 2) | Data processing supporting technologies | Period 2, Monday morning | 2 |
| Large Scale Distributed Systems (Period 1) | Data processing supporting technologies | Period 1, Friday afternoon, TIME SCHEDULE CONFLICT | 2 |
| Content distribution in wireless networks (Period 1) | Data processing supporting technologies | Period 1, Wednesday morning | 2 |
| Evolving internet (Period 1) | Data processing supporting technologies | Period 1, Friday morning | 2 |
| Techniques modernes de programmation concurrente (Period 1, in French) | Data processing supporting technologies | Period 1, Tuesday afternoon | 2 |
| Knowledge Engineering (Period 1) | Application of data science, in particular on multimedia content and data on the web | Period 1, Tuesday afternoon (prerequisite: web of data ?, in //) | 2 |
| Middleware for the Internet of Things (Period 2) | Data processing supporting technologies | Period 2, Tuesday morning | 2 |
| Advanced image processing (Period 1), evolution in progress with more Machine Learning content | Application of data science, in particular on multimedia content and data on the web | Period 1, Thursday morning | 2 |
| Réalité virtuelle (Period 2, in French) | Application of data science, in particular on multimedia content and data on the web | Period 2, Thursday afternoon | 2 |
| Interagir dans un monde 3D (Period 1, in French) | Application of data science, in particular on multimedia content and data on the web | Period 1, Wednesday morning | 2 |
| Ingénierie 3D (Period 1, in French) | Application of data science, in particular on multimedia content and data on the web | Period 2, Monday afternoon | 2 |
| French as a Foreign Language (beginner or intermediate). On top of program whenever timeschedule allows it. (Period 1) | Period 1, Wednesday afternoon | ||
| Refresher in Maths, Probas and Stats. On top of program | Blocked full days: 5,6,9, 11 of sept. 2019 |
Innovation and Entrepreunership module (6 ECTS)
Besides, the student must develop a mandatory Innovation and Entrepreneurship (I&E) work of 6 ECTS, as mandated by EIT Digital I&E common specification of masters. This work is coached by the UNS local coordinator in I&E and spans the whole October-February period once per two weeks approximatively, on Wednesdays 1 to 4 pm, starting Oct 16, 2019. The goal is to reuse on-line I&E material from Sakai, common to all EIT Digital masters, and apply this to selected business cases. These business cases are most of the time proposed by the various EIT Digital Action Lines partners. More (even if old, so perhaps not so up-to-date) details here.
Semester 2, March-August full time (30 ECTS, 18 weeks minimum, 6 months max)
Internship/Master thesis
This internship can be done either in our partner research institutions teams at I3S, LJAD, LEAT, INRIA even if for EIT Digital students, industrial internships are the preferred choice. We provide support and guidance to this aim. Including for outside the Nice - Sophia-Antipolis Technology park. The evaluation of the internship work encompasses three aspects: work achieved as measured by the internship supervisor, written thesis submitted at the end of August and evaluated by the university supervisor, oral defense organized early September (can happen in visio conference mode) and evaluated by a jury of professors. Positions as employee in a company can also be turned as the mandatory period for preparing the master thesis, as soon as the content is approved by the head of the master.