Applied MSc in Data Science and AI2018-11-16T16:49:46+00:00

Applied MSc in Data Science and AI

Overview

This 6-month of classes and 6-month internship Applied MSc 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 (part time).

DSTI STUDY MODE

Click here to find more about the study modes

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 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

The Applied Bootcamp

applied_bootcamp_spring_2019

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.

Enterprise-Level Certifications

AWS-Training-DSTI partner Data-ScienceTech-Institute-SAS-Gold-Partner

Programme Structure

Core Courses – 800 hours – 60 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):

Information Systems – 150hrs

  • Computer Science & IT
    Classic Design & Programming
    Object-Oriented Design & Programming
  • Data Wrangling with SQL Advanced SQL queries, dynamic SQL, stored procedures & triggers
  • Semantic Web for Data Science Representing and querying web-rich data (RDF, SPARQL), Introducing Semantics in Data (RDFS, Ontologies), Tracing and following data history (VOiD, DCAT, PROV-O)

Core Data & Artificial Intelligence – 250hrs

  • Applied Mathematics
    Calculus – Linear Algebra – Trigonometry & Complex Numbers
  • Continuous Optimisation (Mathematics)
    Critical points, multiple variables function optimisation, gradient methods, constraint-based optimisation with Lagrange Multiplier
  • Metaheuristics Optimisation (Computer Science)
    Applied Numerical Optimisation and MSDO – Constrained and unconstrained, linear and non-linear, genetic algorithms (Particle Swarm Optimisation, Simulated Annealing, etc.)

  • Foundations of Statistical Analysis and Machine Learning
    Probabilities and distribution – Tests – Inference – Regression – Clustering
  • Advanced Statistical Analysis and Machine Learning
    CART and Random Forests and applications to Map/Reduce – Features Selection & Engineering
    Models Comparison & Competition
  • Artificial Neural Networks
    Data representation and distributed representations, Universal Interpretation Theorem, Probabilistic Interpretation, backpropagation and stochastic gradient descent
  • SAS Institute “The SAS ecosystem DSTI Chair” **
    SAS /Base & SAS/STAT

    Preparation for SAS Certified Predictive Modeler Using SAS Enterprise Miner 14

Applied Data Science & Artificial Intelligence – 150hrs

  • Survival Analysis using R
    Probabilistic description of Survival data, parametric, non-parametric and semi-parametric (Cox model) statistical methods. Applications to Big Data with penalised Cox regression
  • Deep Learning with Python
    Introduction to PyTorch, – Deep Learning, Neural Architectures and their applications – Neural Network training on a GPU (practice)

  • Time-Series Analysis using SAS
    Forecasting Using SAS Software: A Programming Approach (SAS/ETS)
  • Agent-Based Modelling for population behaviour
    Modelling objectives, model types, matching modelling approaches to studies objectives, ODD protocol, ABM objectives and components
  • The Hadoop & Spark ecosystem
    HDFS, scheduling & resources management
    Workflow management & ETL, Dataflow management, Scalable Enterprise Serial Bus
    Realtime processing, Machine Learning, Data Exploration & Visualisation

Management, Ethics & Law – 50hrs

  • Data ownership and protection laws and regulation
    Private Data – Corporate Data
    EU Data Protection Act, GDPR, US-EU Data Transfers regulations
  • Project Management: PMP-PMI and Agile Approaches
    PMBOK (PMI) – Agile Approaches – Kanban

* 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.

Admissions

Learn more about the application deadlines

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Admission Requirements

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Tuition Fees

The following tuition fees are expressed exclusive of any taxes & are in effect for the Spring 2019 entry and are subject to change for future years. Tuition fees for the Autumn 2019 entry will be published in Spring 2019.

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.

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ON-CAMPUS
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ONLINE
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SPOC

On-campus, non-EU and mature students (>28 y/o) may be required by the French Government to pay an extra for the CVEC. This obligation and extra cost is only collected by DSTI on behalf of and for the French Government.

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.

Click here to find more about the study modes.

Work Placement

DSTI_data_science_big_data_programmeOnce 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.

Examples of internships

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Download the Couthon Conseil Guide (french only)
to have an overview of the most important jobs in the data field
.

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“ We meet a lot of nationalities and this helps us to develop ourselves in the data science field and to exchange with everyone. Also, we work on real projects and this allowed us to apply and improve what we learned throughout the year on a real professional case ”

– Nehmy Forbin | Applied MSc in Data Science and AI | Big Data Consultant at Arago Consulting

“15 months ago, I would have never imagined that a program like DSTI would open so many doors for me, allowing me to learn one of the most interested fields in this century, and helping to acquire the technical skills to be completely aligned with my company strategy and my personal projects.”


-Nicolas Aguirre Dobernack Applied MSc in Data Science and AI | Security Technology Services Manager at Citrix

Our programmes

APPLIED MSC IN DATA SCIENCE AND AI

APPLIED MSC IN DATA ENGINEERING

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Contact Info

Les Templiers
950 Route des Colles
06410, Biot

Phone: +33 (0) 171182402