International Executive MSc in Applied Data Science & Big Data

SPOC Applied MSc in Data Science
Discover the heart of Artificial Intelligence
Online Professional Part-Time Education – Small Private Online Course (SPOC) Degree Programme

degree programme
Applied MSc


HD recorded
with unlimited

SPOC dedicated
extra time
live professors' assistance

Tuition fees*

*Tuitions fees are exclusive of any local taxes (e.g. VAT, Sales Tax, etc.) which may apply in the students’ country of residence
Self-funded students are normally exempt of French/EU VAT collection

Discover the programme structure
SPOC MSc in Applied Data Science & Big Data Schedule
SPOC MSc in Applied Data Science & Big Data Schedule
SPOC MSc in Applied Data Science & Big Data World Map


Key benefits of our
Small Private Online Course (SPOC)
Applied MSc programme

  • Identical content to our Applied MSc in Data Science degree programme.
  • Part-time schedule, with “study time” / “free periods” between courses giving time to watch the HD class recordings.
    Access to the recordings is unlimited during the programme as well as after graduation.
  • Live meetings with professors for support and Q&A during the “free periods”.
    For every 25hrs of classes, you get 4hrs of live & recorded professors time through distinct meetings in the Americas & EMEA to South Asia zones (96hrs in total over the whole programme).
  • 24/7 access to all teaching materials and private online interactions (forums, chats, etc.) via Moodle, our Learning Management System.
  • Group work for the “Engineering Projects” is organised by timezones: one set of students for the Americas, one for EMEA to South Asia .
    SPOC students are not left by themselves to passively watch recordings: they collaborate together and belong to an interactive DSTI cohort.
  • Access to live classes off-campus or on-campus at your availability & leisure.

This 18-month part-time Applied MSc degree programme in SPOC mode, 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.

France has a long-standing history of excellence in analysis and design of complex information systems as well as a celebrated talent for mathematics, the essential foundation for becoming a Data Scientist as described on our page “How to become a Data Scientist?”.

Read our infographic to make the right choice between the Applied MSc in Data Science and Data Engineering.

Classes are given exclusively in English from the:

  • Beginning of October of year X to end of March of year X+2 for the Autumn entry
    (e.g October 2nd 2017 to March 30th 2019);
  • Mid-March of year Y to mid-October of year Y+2 for the Spring entry
    (e.g March 12th 2018 to October 9th 2020);

The sequence of classes unfolds as depicted on the picture beside. The frequency of classes is more intense during the first two semesters (225hrs per semester) and lighter on the third (150hrs).
By the end of the 18-month period, SPOC MSc students are given an extra 6-month period to take the SAS & AWS Certification examinations.

Classes for this SPOC Applied MSc programme are recorded every day. One day of recording amounts on average to 5hrs to watch. Each course lasts for either one week (25hrs) or two weeks (50hrs).

In this SPOC Applied MSc degree 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.
  • be trained to and take two Enterprise-Level Certifications examinations:
2 Enterprise-Level Certifications

Amazon AWS *Cloud-Computing DSTI Chair*
Preparation for AWS Certified Solutions Architect – Associate

WS Certified Solutions Architect - Associate

SAS Institute *The SAS ecosystem DSTI Chair*
Preparation for SAS Enterprise Miner certification

Data ScienceTech Institute SAS Gold Partner Logo

SPOC MSc in Applied Data Science & Big Data SPOC World Interaction

This SPOC Applied MSc 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

  • Distributed Architecture (IS1)
  • Amazon AWS “Cloud-Computing DSTI Chair” **
    Preparation for AWS Certified Solutions Architect – Associate
  • Software Engineering (IS2)
  • Computer Science & IT
    Classic Design & Programming
    Object-Oriented Design & Programming
  • Data Management (IS3)
  • 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 Science & Artificial Intelligence

  • Foundations (DSBD1)
  • 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.)
  • Data Science & Artificial Intelligence (DSAI2)
  • 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

  • Practical Data Science & Artificial Intelligence (ADSAI1)
  • 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 and behaviour modelling (ADSAI2)
  • 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
  • Distributed Computing for Data Science (ADSAI3)
  • 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

  • Data regulations (MEL1)
  • Data ownership and protection laws and regulation
    Private Data – Corporate Data
    EU Data Protection Act, GDPR, US-EU Data Transfers regulations
  • Project Management (MEL2)
  • 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.


All students will be assigned engineering projects attached to the courses. Students will conduct projects throughout the year until their classes finish. 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.

The following tuition fees are expressed exclusive of any taxes & in effect for the Autumn 2018 entry and are subject to change for future years.
Tuition fees for the Spring 2019 entry will be published in October 2018.

Tuition fees may be subject to the local taxes of your country of residence. 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.

The programme tuition fees are spread into 3 instalments over one year.

SPOC MSc in Applied Data Science & Big DataEntryTuition Fees (exclusive of any potential taxes)
Tuition feesAutumn 201813,500€

Should your employer be willing to sponsor your SPOC MSc matriculation, 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.

Applicants with a 3-year
BA, BSc or BEng degree

3 years of relevant work experience

Applicants with a 4-year
BA, BSc-BEng or MA-MSc-MEng degree

Relevant work experience

Applicants with a 5-year
MA, MSc – MEng or Chartered Engineers

No particular conditions