This 6 months of classes and 6-month internship Applied MSc 1 programme, with its two entries in Autumn and Spring, is a programme designed to bring students to the scientific heart of Data Science and Artificial Intelligence.
Classes for this Applied MSc programme are offered on a full-time basis from DSTI campuses (around 5hrs a day), Online or in SPOC mode (self-paced and montlhy intakes).
This programme is “depth-first” in applied mathematics and their implementation, led by Professors from the “French School of Mathematics”. It aims to give students a deep understanding of the main scientific grounds for artificial intelligence techniques, centred on modelling and then implementing rather than surveying data science APIs & frameworks.
Prospective students seeking for an IT-focused, “breadth-first” through programming frameworks, should be looking at our Applied MSc in Data Engineering for Artificial Intelligence programme instead.
Classes are given in English from the:
- End of September to beginning of April for the Autumn entry;
- Beginning of March to mid-October for the Spring entry.
On a full-time basis (5 hours/day) along with “Engineering Projects” and followed by a 6-month work placement.
In this Applied MSc programme, you will:
- Sharpen your applied mathematics for data science and artificial intelligence;
- Focus your learning curve on understanding the heart of artificial intelligence algorithms;
- Operationalise your scientific skills with the analysis, design, implementation & monitoring of IT & Big Data architectures;
- Combine science and technology in application courses & projects requiring both, for dealing with industry-grade data science;
- Get awareness of IT project management and the legal consequences of data handling, with a pinch of ethical thinking regarding the consequences of mining (big) data.
If you are currently in employment and/or can benefit from third-party financing due to lifelong education rights, please get in touch with us to check what could be organised.Infographic – Data Science VS Data Engineering
Infographic – Students Profile
1 Once your studies and professional experience are completed, your achievements will be assessed by our Graduation Committee. If successful, you will be able to obtain the degree “Expert en Sciences des Données” (Experts in Data Science). DSTI is proud of its Applied MSc in Data Science & AI and Applied MSc in Data Engineering for Big Data to have been fully accredited at Master’s level by the French Government via the RNCP mechanism. The RNCP “Répertoire National des Certifications Professionnelles” is a government recognition mechanism dedicated to scrutinising programmes’ suitability for the work market. A RNCP title rewards specific needs in terms of skills and knowledge transfer for immediate employability, which is the heart of DSTI philosophy.
The Applied Bootcamp
Data ScienceTech Institute is offering all future students a Bootcamp to get you up to speed on skills required to start leveraging the different topics of our Applied programmes. This Applied Bootcamp lasts 10 days (50 hours of classes) and can be followed On-Campus and Online.
This is not mandatory but it is a good preparation to start the programme the best possible way.
Next dates : From Monday February 3rd to the 14th, 2020
Discover the Bootcamp programme for the Spring 2020 intake !
Programme Structure 1
Core Courses – 800 hours – 60 ECTS
The internship is equivalent to 30 ECTS.
This Applied MSc programme programme is composed of all the following modules*, which are actual hours of class presence (personal work is expected on top of these):
* Please note that course content and support technologies may vary when delivered according to job market needs and under the supervision of Data ScienceTech Institute Scientific Advisory Board.
** Provided you are not subject to any Sanction Programmes of the United States of America which would affect your rights to take these classes and/or examinations.
Engineering Projects – 200hrs
All students will be assigned engineering projects attached to courses of programme. Students will conduct projects throughout the year until their classes finish and they go to their work placement . These Engineering Projects aim to apply all the knowledge and skills acquired in the different classes and to use DSTI professors as mentors and coaches throughout the year. Some of these projects may come from applied research work done by our Professors affiliated to a research lab.
1 Once your studies and professional experience are completed, your achievements will be assessed by our Graduation Committee. If successful, you will be able to obtain the degree “Expertise Science des Données” (Expertise in Data Science). This degree is a Masters’, which means a level 7 on the European Qualifications Framework and level 1 on the French framework. An application had been filed for DSTI in order to be registered in the National Register of Professional Certifications (RNCP, file #1553) of “France Compétences” (formally CNCP), for the degree to be countersigned by the French Government. This procedure takes from 8 to 18 months. If the outcome is positive, all DSTI graduates (past and current) will be able to take advantage retroactively of this registration in the RNCP, according to the L335-6 article of the French Code for Education (Code de l’Éducation).
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The following tuition fees are expressed exclusive of any taxes & are in effect for the Spring 2020 entry and are subject to change for future years.
Off-campus students tuition fees may be subject to the local taxes of your country of residence. On-Campus self-funded students are normally exempt of French/EU VAT collection.
In any case, please get in touch with us to check which scenario applies.
Tuition fees for the Spring 2020 intake:
* The following tuition fees apply only to students living outside of France. Online Education students living in France are considered “On-Campus” and therefore the “On-Campus” tuition fees apply.
** The VAT applies to students living in France.
On Campus students, whose registration fees are not covered by a third party organisation, must pay the CVEC student tax (90€). In addition, students who are not yet registered for social security can register online for student social security on the Ameli website. European students will be required to provide the membership number on their European Health Insurance Card.
Once admitted, you will be required to pay 10% of the programme fees for On-Campus students and 20% for Online Education in order to secure your enrolment (wire transfer, debit/credit card).
This payment can only be refunded in case of exceptional circumstances for not enrolling the programme: visa not issued for international students or proven sudden change of financial situation. Any refund due to visa refusal is exempt if the refusal if due to financial reasons / insufficient funding.
The tuition Fees are paid in 3 instalments, every two months in advance (w/exc. of the initial 10% (on-campus) or 20% (off-campus) down payment for securing your enrolment).
Should an employer be willing to sponsor your Applied MSc matriculation during a sabbatical, we would deal directly with your HR department regarding the fees proportion eligible to be covered in lieu. Please note that French/EU VAT collection may apply to fees paid by your sponsor.
Once the classes are finished, our Applied MSc students can choose between going for a work placement or working on an advanced engineering project and dissertation. DSTI strongly encourages On-Campus students towards industrial placement and advanced engineering projects for online education students ones.
The online career platform allows each student and alumni to have the necessary tools to boost their career in the data field. Students will be able to find internships and job opportunities through a personalized profile. They will access exclusive opportunities across Europe.
“DSTI’s course and syllabus are continuously evolving according to the needs of the industry and the school makes sure that its students receive the best of the knowledge in the field of analytics that makes them highly employable”