International Executive MSc in Applied Data Science & Big Data

SPOC MSc in Applied Data Science & Big Data
Online Professional Part-Time Education – Small Private Online Course (SPOC) Degree Programme

Part-Time
Profesionnal
0-month
degree programme
Applied MSc

Enterprise-
Level
0
Industrial
Certifications

HD recorded
tuition
0hrs
with unlimited
replay

SPOC dedicated
extra time
0hrs
live professors' assistance

Americas
Timezones
0$
Tuition fees*

EMEA to South Asia
Timezones
0
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

PART-TIME PROFESSIONAL PROGRAMME
STUDY WHILE YOU WORK

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

  • Identical content to our MSc in Applied Data Science & Big Data 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 designed to open your career to these Big Data Analytics jobs all industries are looking for.

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?”.

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:

  • learn how to understand the analysis, design, implementation & monitoring of IT & Big Data architectures;
  • get familiar with machine and deep learning algorithms with an industrial approach to applied mathematics;
  • learn how to deploy Big Data architectures and Machine Learning results into corporate systems and get familiar with data visualisation;
  • get awareness of 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
SPOC MSc in Applied Data Science & Big Data SPOC Schedule Template

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
0hrs

  • Architecture (IS1)
  • Amazon AWS “Cloud-Computing DSTI Chair” **
    Preparation for AWS Certified Solutions Architect – Associate
    Big Data and Machine Learning on Amazon AWS
  • Software Engineering (IS2)
  • Analysis and Design of Information Systems
    Refreshers in Computer Science: fundamentals of algorithmics
    & data structures using C & C++
    Analysis methodology, E/R model & LAPAGE method for data model design
  • Databases (IS3)
  • Data Wrangling backed with MS SQL Server
    Advanced SQL queries, stored procedures & triggers (T-SQL)
    Combining SQL and .Net code for complex ETL (SSIS)Dynamic Reporting and BI (SSRS)
  • Semantic Web (IS4)
  • Integrating Semantic Web technologies in Data Science developments
    Representing and querying web-rich data (RDF, SPARQL), Introducing Semantics in Data (RDFS, Ontologies), Tracing and following data history (VOiD, DCAT, PROV-O)
Applied Data Science & Big Data
0hrs

  • Foundations (DSBD1)
  • Applied Mathematics for Data Science
    Calculus – Linear Algebra – Trigonometry & Complex Numbers
  • Algorithmics for Data Science – Optimisation
    Combinatorics and Complexity – Graph-based modelling & algorithms for discrete optimisation
    Introduction to continuous optimisation
  • Machine and Deep Learning (DSBD2)
  • 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 Network and introduction to Deep Learning
    Data representation and distributed representations, Universal Interpretation Theorem, Probabilistic Interpretation, backpropagation and stochastic gradient descent
  • SAS Institute “The SAS ecosystem DSTI Chair” **
    Preparation to SAS Certified Predictive Modeler Using SAS Enterprise Miner 13
    SAS and Hadoop – SAS Visual Analytics – Base SAS
  • MapReduce Ecosystem (DSBD3)
  • The Hadoop & SPARK ecosystem
    HDFS, scheduling & ressources management
    Workflow management & ETL, Dataflow management, Scalable Entreprise Serial Bus
    Realtime, Machine Learning, Data Exploration & Visualisation
Business & Industrial Applications
0hrs

  • Marketing (BIA1)
  • Time-Series Analysis using SAS
    Forecasting Using SAS Software: A Programming Approach (SAS/ETS)
    Forecasting Using SAS Forecast Server Software
  • Operations (BIA2)
  • 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
  • Project Management (BIA3)
  • IT Project Management: PMP-PMI and Agile Approaches
    PMBOK (PMI) – Agile Approaches – Kanban
  • Social Sciences (BIA4)
  • Agent-Based Modelling for population behaviour
    Modeling objectives, model types, matching modelling approaches to studies objectives, ODD protocol, ABM objectives and components
  • Modelling complex and chaotic economic systems with System Dynamics
    Causal loop diagrams, Stock and flow diagrams, Non-linear algrebraic equations, Chaos Theory
Ethics & Law
0hrs

  • Data regulations (L1)
  • Data ownership and protection laws and regulation
    Private Data – Corporate Data
    EU Data Protection Act, GDPR, US-EU Data Transfers regulations

* 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
0hrs

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 OCTOBER 2017 entry and are subject to change for future years.
Tuition fees for the MARCH 2018 entry will be published in October 2017.

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.

80% of the programme tuition fees are spread into 12 monthly instalments over one year.
The remaining 20% is to be paid by the end of the programme, regardless of success (graduation) or failure.

Students in the Americas zone may request to pay the fees in euros.

Students in the EMEA (except for students living in the European Union and/or the European Economic Area) to South Asia zones may request to pay the fees in US dollars.

SPOC MSc in Applied Data Science & Big DataEntryTuition Fees (exclusive of any potential taxes)
Americas timezonesAUTUMN 201716,800$ (USD)
EMEA to South Asia timezonesAUTUMN 201711,800€

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