Applied MSc in Data Engineering2018-11-16T16:49:20+00:00

Applied MSc in Data Engineering

Overview

This 6-month of classes and 6-month internship Applied MSc programme, with its two entries in Autumn and Spring, is designed to open your career to these Big Data Engineering jobs all industries are looking for.

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

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:

  • 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.

Infographic – Data Science VS Data Engineering
Infographic – Students Profile

The Applied Bootcamp

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Data ScienceTech Institute is offering all future students a Bootcamp to get you up to speed on skills required to start leveraging the differents 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 Cloudera certification_DSTI

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):

Data Management – 150hrs

  • 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
  • The Hadoop Ecosystem
    HDFS, MR, YARN, SPARK
  • Data Pipeline
    Classic ETL solutions – Cloud-based solutions with AWS Data Pipeline & AWS Kinesis – Open-source solution with Apache Kafka & Beam

Data Science – 100hrs

  • 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 on GPU
    Recurrent Neural Networks, LSTM, Residual Networks

Distributed and Performance Programming – 100hrs

  • 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 – 150hrs

  • Design of Information Systems
    Algorithmics approaches to relational data modelling and object-oriented programming
  • 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 – Leveraging Visual Studio for DevOps – Continuous Integration with Jenkins & Kubernetes
  • Cybersecurity
    System Security Design Patterns – Network security – Data at-rest and in-transit encryption – Code safety – Application to blockchain technologies

Cloud & IT – 100hrs

  • Amazon AWS & Microsoft Azure
    Preparation to AWS Certified Solutions Architect – Associate Certification – Comparative overview of Microsoft Azure
  • 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.

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

How to apply?

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).

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_programme

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.

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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Ali Kabbadj DSTI

“I apply notions from DSTI as statistics, coding (python), SQL, web semantic and deep learning. DSTI’s broad vision of data science helped me to have enough self-confidence to look for innovative way to response to the challenges.”


Ali Kabbadj | Applied MSc in Data Science and AI | Data Scientist at Assystem Paris

DSTI Raul Mora

“The MSc in Data Science is versatile enough to show us a wide range of paths to take afterwards. Now I am clear about which one to follow so I am focusing my efforts on that.”


Raul Mora | Applied MSc in Data Science and AI | Student at DSTI Paris Campus

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