Master Data Science

2 Years | 120 Credits

Objectives

The Master " Data Science"The objective of the "Data Science" Master's degree is to provide in-depth training on how to design, optimise and implement complex systems, using the most recent technologies in the fields of "BIG DATA" and data mining, integrating skills in computer science (complex systems and high-level programming), applied mathematics, digital humanities, and language industries (data and text mining) . This master's degree aims first of all at the reconversion of the cohort of graduates in mathematics. Indeed, with a double competence in mathematics and computer science, the graduates of this master will meet a very strong need of Tunisian and international companies.

Admission requirements

To be admitted to a Master's programme, you must have the minimum diploma required for the level of training you are aiming for

  • Access to the first year of the Master's programme (M1):- Hold a Bachelor's degree in Computer Science, Mathematics, Computer Science Management, or equivalent,- Pass the admission interview.
  • Access to the second year of the Master's programme (M2) :- Successful completion of the first year of a Master's degree in one of the Big Data specialties - Successful completion of the admission interview

Targeted competences

The Professional Master's Degree " Data Science "This is the first time that a company has been asked to meet this need for skills by training future managers:
  • Quickly operational in missions in the field of BIG DATA, thanks to the acquisition of fundamentals, case studies and practice on concrete problems.
  • Responsible, through understanding the ethical, privacy and sustainability issues facing international business and society today.
  • Having, thanks to their scientific and technical skills, mastered the masses of data allowing them to analyse and extract knowledge to help make strategic decisions and create innovative services.
  • Able to help organisations create value from massive data: product innovation, process innovation, marketing, new business models...

Targeted occupations

The course of this professional master's degree leads to working life.
The intended occupation : Data Analyst
Graduates will be able to either :
  1. Working in public or private companies whose niche includes massive data mining. Web engineering or social networks.
  2. Entering large companies requiring the creation and exploitation of very large data banks, in research and development, on high level applications and on process and flow optimisation.

Certifications offered

    • MOS2 Excel
    • IBM Big Data

    • Registration fees

    All costs mentioned are exclusive of VAT (the current rate in January 2020 is 7%)

    Duration Type of Fee Tunisian students International Students
    2 years Application fee
    (payable only once on first enrolment in a PI course)    		 700 DTTTC 250 € INCL. VAT
    Annual registration fee 7450 DTHT 3400 € EXCL.
    Annual enrolment fee (special times) 5750 DTHT 2100 € EXCL. TAX

    Cursus

    Semester 1

    Code Module Credits
    EU1 Mathematical Foundations of Scientific Data 2
    EU1 Graph and applications 3
    EU1  Workshop Statistics with R 2
    EU2  Introduction to Big Data 4
    EU2  Parallel and Distributed Computing 3
    EU3  NoSQL database 3
    EU3  Database Management System PL_SQL 3
    EU4  English 1 2
    EU4 Communication Technique 1 2
    EU4 Corporate Culture 2
     EU5  Object Oriented Programming (Java) 2
     EU5 Analytical Database Processing (SAS) 2
    EU5 Data analysis 2

    Semester 2

    Code Module Credits
    EU6 Machine Learning 1 2
    EU6 Data mining 3
    EU6 Data Mining and Machine Learning Workshop 2
    EU7 Advanced Big Data Processing 4
    EU7 Systems Modelling for Big Data 3
    EU8 Distributed Systems for Big Data 3
    EU8 Decision-making information system 3
     EU9 English 2 2
    EU9 Communication Technique 2 2
    EU9 Business creation 2
     EU10 Stochastic process 2
     EU10 Agile Unified Development Process 2
    EU10 Mathematical foundation for signal processing 2

    Semester 3

    Code Module Credits
    EU11 Machine Learning 2 (Deep Learning) 2
    EU11 Massive Data Mining 3
    EU11 Federative Machine Learning Project 2
    EU12 Automatic Natural Language Processing 4
    EU12 Cloud environment for Big Data 3
    EU13 Big Data Frameworks federating project 3
    EU13 Analysis and Programming with Python 3
     EU14 English 3 2
    EU14 Business Management 2
    EU14 Computer law and ethics 2
     EU15 Service Oriented Architecture 2
     EU15 Block Chain Internet of Things and smart systems 2
    EU15 Combinatorial optimisation 2

    Semester 4

    Code Module Credits
    EU16 Internship 30
    30

    Register now



      Head of Department

      ASMA BEN AMMAR

      +216 99 333 124

      a.benammar@pi.tn