International Executive MSc in Applied Data Science & Big Data

SPOC Applied MSc in Data Data Engineering
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 Engineering 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.

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 Cloudera & 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:

  • Learn how to understand the analysis, design, implementation & monitoring of IT & Big Data architectures;
  • Leverage the most prevalent programming languages and their libraries for applied machine and deep learning;
  • Learn how to architect and deploy highly distributed data and computation clusters such as Hadoop, SPARK or Microsoft Orleans;
  • Discover the DevOps world and set up continuous integration architecture;
  • 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

Cloudera Certified Data Engineer
Preparation for Cloudera Certified Data Engineer

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):

Data Management

  • Data Bases
  • Relational Databases Management Systems
    Using MySQL & Microsoft SQL Server: stand-alone and cluster deployments, integration in software, ETL, persistence frameworks
  • Advanced SQL for Data Wrangling
    Complex joins & subqueries, stored procedures & triggers
  • NoSQL databases
    Key-value store, Document store, Graph database , hybrid approaches with Apache Cassandra
  • Big Data
  • The Hadoop Ecosystem
  • Data Pipeline
    Classic ETL solutions – Cloud-based solutions with AWS Data Pipeline & AWS Kinesis – Open-source solution with Apache Kafka & Beam
Data Science

  • Machine learning
  • Foundations of Statistical Analysis & Machine Learning
    Distributions – Descriptive & Inferential Statistics – Classification & Regression Trees
  • Machine Learning with Python
    Language fundamentals & common frameworks for machine learning: NumPy, SciPy, scikit-learn
  • Machine Learning with R
    Language fundamentals, recursive and functionnal programming, data frames, common machine learning packages
  • Deep Learning
  • Deep Learning on GPU
    Recurrent Neural Networks, LSTM, Residual Networks
Distributed & Performance Programming

  • Programming langages for Data Engineering
  • C & C++ for Distributed Computing
    Portable and scalable large-scale parallel applications using OpenMP & OpenMPI
  • Java & Scala programming
    Java for Map Reduce in Hadoop & Scala for SPARK
  • Microsoft .NET for Distributed Computing
    Task Parallel Library – Asynchronous programming – Orleans framework for distributed systems
  • Scientific Programming
    Fundamentals in Fortran & MATLAB, Fortran for R packages, MATLAB with C/C++
Operational Methodologies

  • Information Systems
  • Design of Information Systems
    Algorithmics approaches to relational data modelling and object-oriented programming
  • DevOps
  • Software Engineering Project Management & Quality
    PMBOK (PMI) – Agile Approaches – Kanban – Quality Metrics – Unit & Integration testing
  • DevOps & Continuous Integration
    The DevOps toolbox: Nagios, Consul, Docker, Ansible, GitHub – Levaraging Visual Studio for DevOps – Continuous Integration with Jenkins & Kubernetes
  • Cybersecurity
  • Cybersecurity
    System Security Design Patterns – Network security – Data at-rest and in-transit encryption – Code safety – Application to blockchain technologies
Cloud & IT

  • Cloud Computing
  • Amazon AWS & Microsoft Azure
    Preparation to AWS Certified Solutions Architect – Associate Certification – Comparative overview of Microsoft Azure
  • IT Fundamentals
  • Semantic Web
    Representing and querying web-rich data (RDF, SPARQL), Introducing Semantics in Data (RDFS, Ontologies), Tracing and following data history (VOiD, DCAT, PROV-O)
  • IT Foundations for Data Engineering
    Computer Architecture – Operating Systems & Virtualisation – Networking

* 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