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:
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/0/invite, in Promotions/Emploi du Temps/Année, choose Master 2 IFI GMD DSC (will shortly be renamed 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 to happen probably the Sept 4th afternoon at Polytech 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. Most probably on the Wednesday 11 of sept.
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 are still under time schedule incertitude. Days is certain, but start/end periods)

Elective courses list from 2019-20 Topic Schedule Coeff
Statistical machine learning (see p2) (approx. end of Period1/Period 2) Data modeling and analysis Thursday afternoon, from 12/09/19 (time schedule to be confirmed) (approx 10 lessons), 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, from 05/12/19 (approx 10 lessons), Sciences faculty campus  NIE, 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 (new course 2018-19, syllabus still under construction !)) 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 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.