DSTI Applied MSc in Data Analytics master’s level programme propels you far beyond the conventional analytics training offered by typical business schools. This unique MSc programme delivers an unparalleled blend of advanced mathematics, computational science, and cutting-edge IT practices—all taught in English. By fully integrating deep technical skills into a profound business perspective, we empower you to move from mere insight generation to hands-on implementation and automation of analytics solutions within modern information systems.
Our curriculum is anchored in scientific rigour. You will master advanced statistical methods and their mathematical foundations, gaining the sophistication needed to build robust, production-ready models. Yet we go further: you will immerse yourself in the wealth of IT disciplines—cloud computing, data warehousing, NoSQL databanks, data pipelining, software engineering principles, and more—ensuring you can shape the data ecosystems that fuel and sustain analytics initiatives at scale.
Unlike traditional analytics programmes focused primarily on dashboarding and surface-level insight, the DSTI approach embraces the entire lifecycle of data-driven decision-making. Our graduates do not merely interpret data; they contribute to engineering the pipelines, configuring the infrastructure, and applying machine learning techniques to automate and operationalise analytics across diverse information systems.
At DSTI, you will gain:
By the end of the programme, you will emerge as a versatile, forward-thinking data analytics professional. You will not only conduct data-driven strategies but also integrate, automate, and evolve them continuously—advancing from the confines of conventional analytics into the realm of concrete operational impact.
Apply now to redefine the role of the data analyst and become the driving force behind next-generation analytics implementations.
All DSTI MSc programmes – Key Dates for the 2025 Entries
Application deadlines for:
Induction Days:
Classes start dates:
Application deadlines for:
Induction Days:
Classes start dates:
Please note that Self-Pace Online Course (SPOC) applicants are not subject to any particular application timeline
As a front-runner in data and AI in France, DSTI offers a Bachelor programme at RNCP level 6. Our MSc programmes hold a RNCP level 7 accreditation. DSTI is recognised under the 3IA Cote d’Azur Label for extensive AI content and proudly possesses Qualiopi RNQ certification, affirming the quality of our processes. Our Qualiopi certificate can be downloaded by clicking on this link.
The following are the major objectives of the Applied MSc in Data Analytics programme:
The Applied MSc in Data Analytics programme entitles students to 120 ECTS in full validation. This includes 720 hours of coursework (90 ECTS), with 75 hours of DSTI Warm Up for technical skills, and 40 hours of support sessions. Finally, professional experience, internships or apprenticeships (30 ECTS) provide practical experience in data analytics.
Any course and/or block of courses/skills (teaching unit) validated according to the knowledge assessment procedures automatically constitutes partial validation, with the associated ECTS credits.
24-31 Years
Average age range
80%
International students
5+
Hands-on projects
1
Mandatory International Certification to graduate
DSTI offers the Applied MSc in Data Analytics in two modes: Undergraduate & Postgraduate Education and Executive & Continuing Lifelong Education.
Undergraduate & Postgraduate Education is designed for students under 30 transitioning from school or university, preparing them to become proficient data professionals. Choose between two options: Full-Time or Part-Time (Apprenticeship).
For beginners in Data Analytics, we suggest the 2-year Full-time mode with options for two data-related internships, the second being mandatory.
The apprenticeship mode combines part-time work and study, open only to EU students or those with a long-term visa in France. Read details before applying.
For professionals typically 30 or older, Executive & Continuing Lifelong Education balances career growth and work commitments. It’s perfect for those with relevant experience or tech education, allowing flexible completion of the Applied MSc in Data Analytics on-campus or online.
SPOC is ideal for students balancing studies with regular jobs. Coursework, completed over a flexible duration through recorded lectures, can be supplemented with live online sessions if available. The course duration is tailored to the student’s needs.
DSTI also provides a ‘Part-time Sandwich’ or ‘Contrat de Professionnalisation’. This option is perfect for those aged 30 and above, French speakers, and individuals who are EU/EEA citizens or long-stay visa holders in France.
DSTI School of Engineering provides warm-up courses for the Applied MSc in Data Analytics, ensuring all students, regardless of their background, start with an equal understanding and are able to reinforce their current knowledge to be fully prepared to start the programme.
A comprehensive module that covers mathematical foundations, Big Data Processing, Machine Learning, Statistical Analysis, and Semantic Web Technologies for Data Analytics.
This course covers the basic notions of applied mathematics required to study optimisation and then data science: calculus, linear algebra, trigonometry and complex numbers.
A course that introduces the fundamentals of descriptive statistics, probability theory, and their applications using R programming language for data analysis.
This course teaches how to import, manipulate, transform, visualise, explore, and model very large datasets in R, with a focus on selecting the best data structures for optimal performance.
A course that teaches data cleaning and preparation, data structures, and machine learning tools such as Pandas, Matplotlib, Scikit-learn, Keras, and Numpy, as well as Flask and OpenCV for web applications.
A course that covers representing and querying web-rich data using RDF and SPARQL, introducing semantics in data using RDFS and ontologies, and tracing and following data history using VOiD, DCAT, and PROV-O.
This course on Time-Series Analysis covers the mathematical foundations and practical applications using R, including advanced techniques such as neural networks.
This course covers solving complex problems using Agent-Based Modelling (ABM), comparisons with statistical, Markov and system dynamics approach, and ABM validation for “trustability”.
Tests, confidence intervals, models and assumptions, with a focus on linear models and regression.
This course introduces practical domain applications for Data Analytics in different sectors. It exposes learners to different approaches and methods in analysing data, interpreting and visualising results to answer domain business needs for marketing, finance, industry and risk management
A module covering various aspects of database management, including data wrangling with SQL, data warehousing and ETL, building data pipelines, and exploring NoSQL databases such as Neo4j and MongoDB.
A course that covers the fundamentals of relational databases, advanced SQL queries, stored procedures, triggers using T-SQL, dynamic SQL, and their applications with Microsoft SQL Server for data wrangling and manipulation.
A course that covers the design and implementation of a data warehouse, structuring an Extract, Transform, Load process, and their applications using Microsoft SQL Server in stand-alone and cluster deployments.
A course that provides preparation for the Neo4j certification, covers graph-based problem modelling, and implementation with the Neo4j graph database for NoSQL data management.
A course that covers the fundamentals of MongoDB databases, collections, and documents, advanced MongoDB queries and aggregations, MongoDB data architecture, and their applications using MongoDB and Robo3T for NoSQL data management.
A course that covers XML data flow, DTD and schemas, XSL transformations, JSON, and their transformations, and how to build efficient and scalable data pipelines.
This course provides comprehensive preparation for the AWS Certified Solutions Architect – Associate Certification, covering the fundamentals of AWS architecture, design, deployment, and operations.
This course covers the fundamentals of algorithmics and data structures using classical design and programming, with a focus on practical applications in C programming language.
A course that covers the fundamentals of algorithmics and data structures using object-oriented programming, with a focus on practical applications in C++ and Python programming languages.
A module that covers various aspects of Data Management and visualisation, including advanced Excel techniques for Data Analytics, CRM Data Management, Data and machine learning visualisation ecosystem, and reporting and visualisation tools.
A course that covers advanced Excel formulas, data visualisation techniques, PowerPivot, Solver, and Visual Basic for Application programming, and their applications for data analytics and machine learning.
A course that covers the data visualisation and machine learning ecosystem, with a focus on tables and machine learning using SAS Viya.
Global approach to modelling – design-independent analysis methodology and model – Formal and semi-algorithmic data model design methods.
A course that covers the preparation for the analyzing Data with Microsoft BI (PL-300) certification and its applications in reporting and data visualisation.
A course that covers the preparation for the Microsoft Power Platform Functional Consultant (PL-200) certification, and its applications in Customer Relationship Management (CRM) data management.
A module that covers IT project management and delves into project management principles using both Traditional and Agile methodologies, as well as exploring data laws and regulations, and the philosophies, geopolitics, and ethics involved in data analytics.
The course covers the principles and frameworks of data privacy and security, including EU & USA regulations, GDPR, Safe Harbour & Successors, and the differences between common law and code law.
Best practices for project management, being in waterfall cycle, agility or just-in-time. Study of PMBOK (Project Management Body Of Knowledge) and Agile (Scrum) approaches.
After each course, students get 4-5 weeks for revision, with additional support sessions available for any questions. These support sessions ensure individual support from our professors.
Our curriculum enables students to prepare for the following certifications
One of which is necessary to graduate (Neo4J Certified Professional). One other certificate is highly recommended for employability but is not mandatory for graduation.
Following are some of the professors who teach the Applied MSc in Data Analytics programme.
Dean & CEO
Sebastien Corniglion is the CEO and co-Founder of DSTI. He is an accomplished Data Engineer, with expertise in CRM, OSS/BSS & ERP systems. He has studied at Université Côte d’Azur & The University of Edinburgh.
Vice-Dean
Hanna Abi Akl is a notable scientist, author, and researcher in the fields of language, logic, and artificial intelligence. His expertise lies in language structure and symbolic and graph-based knowledge retrieval methods within AI.
AWS Academy, from which DSTI was one of the first French institutions to be accepted, provides higher education institutions with a ready-to-teach cloud computing curriculum that prepares students to pursue industry-recognised certifications and in-demand cloud jobs. AWS Academy curriculum helps educators stay at the forefront of AWS Cloud innovation so that they can equip students with the skills they need to get hired in one of the fastest-growing industries.
Again, as one of the first French institution members of the Microsoft Learn for Educators (MSLE), DSTI faculty can easily integrate AI Skills, technical skills, and industry-trusted and verified credentials into their curriculum to set students up for real-world success.
Azure for Education offers students access to an impressive library of fully licensed Microsoft software, developer tools, and cloud resources, including a yearly $100 voucher. These resources are vital for learning and completing AI-related projects, leveraging the Microsoft cloud ecosystem.
O’Reilly is a comprehensive platform providing over 60,000 books, 30,000 hours of video, live events, and interactive labs on topics like cloud computing, software development, AI, and machine learning. It offers students extensive learning resources to deepen their knowledge in AI and related fields.
Students gain access to our partner Adaltas cloud-based cluster, which leverages Hadoop and Spark for processing large-scale data sets. This enterprise-grade cluster provides 24/7 availability, allowing students to experience real-world big data environments.
All students enrolled in the programme receive access to a SAS license. This software suite is essential for advanced analytics, business intelligence, and data management tasks, providing students with tools relevant to AI-based decision-making.
Through DSTI Learn, based on the latest Moodle LMS core, students can access their study materials, including notifications, course schedules, exams, live sessions, recorded lectures, and assignment submissions. This platform ensures students remain connected with their coursework anytime, anywhere.
DSTI offers a support system through Zendesk, allowing students to seek help for academic, career, or administrative queries. Students can also revisit past responses, ensuring continuous support throughout their studies.
DSTI students are provided with lifelong access to an alumni email account, along with Microsoft Windows and Office 365 licenses, enabling them to stay connected and use essential software for professional and personal use.
DSTI Applied MSc in Data Analytics prepares students for promising careers in the data-driven world. An impressive 97% of our students receive internship offers within just 6 months. Furthermore, 2 out of 3 students are presented with CDI offers through our apprenticeships and contrats de professionnalisation programmes.
97%
of students secure an internship offer within 6 months.
1,000€+
average monthly compensation
88%
of students find internships within Europe.
45k€
average starting salary
1,600€
average monthly salary for apprenticeships.
1,950€
average monthly salary for Contrat Pro.
2/3
students receive permanent job offers after their first experience.
50% +
students sign their contracts through DSTI support and guidance.
The admission procedure at DSTI School of Engineering is a selective and competitive, yet inclusive endeavour that provides deserving candidates a fair chance. This outlined admission process applies to all study modes.
Please note that DSTI does not offer parallel admission for direct entry in second year of its Applied MSc programmes.
To qualify for DSTI’s Applied MSc programmes, applicants must satisfy these conditions:
Applicants should have studied Mathematics at high school level or possess an equivalent qualification.
Candidates must have completed a 3 or 4-year Bachelor degree or equivalent from a recognised university.
DSTI provides three ways for prospective students to demonstrate their academic credentials. Students may only submit one type of academic record from the three options provided. However, submitting evidence of more than one qualification listed below will enhance your chances of admission.
Option 1: Minimum Grades + Bachelor Degree Certificate
For consideration into the Applied MSc programme, candidates must attain at least the following grades or their equivalents: USA – GPA 2.0; Germany – 3.5; France – 12; UK – 2:2 (2nd Class Lower Division); India – CGPA 6.5 or Upper second class; China – 67%.
Option 2: standard admission test + Bachelor Degree Certificate
To uphold application quality, we value scores from standardised tests. For the GRE, aim for a minimum of 155 in the quantitative section and an average total score close to 300. For the GMAT, target a minimum score of 42, with an average total score approaching 600.
Option 3: Online DSTI Entry Exam + Bachelor Degree Certificate
If the above criteria are unattainable, consider taking the online DSTI Entry Exam from home. All that’s needed is a computer and stable internet access. The exam comprises two sections: Mathematics and IT.
Since all courses are taught in English, students must have a B2 level of proficiency in English. DSTI will assess English proficiency during the Admission Interview.
To boost an application, students may submit their IELTS or TOEFL scores.
Students at DSTI should have a Windows PC laptop, not Apple Mac, with these minimum specs:
At least Intel Core i5 quad-core or Intel i7 dual-core (or AMD equivalent).
8GB as the absolute minimum, but 16GB highly recommended.
Minimum 512GB, 1TB recommended. SSD required.
It’s a personel choice of investment. If to be done, NVIDIA GPU.
Your PC must be able to run the main latest Windows version (currently: Windows 11).
DSTI will provide a Windows Education (eq. to Enterprise edition) key when classes start.
Don’t purchase MS Office 365: DSTI will provide a full product license when classes start.
The admission process at DSTI School of Engineering is a comprehensive exercise that offers an opportunity to all deserving candidates.
To start your application, browse our various Applied MSc programmes to find your perfect match. Schedule an online meeting with our team for guidance and to check each programme’s tuition fees.
The application is done online, and we assess your suitability. You’ll need to upload standard documents: ID, CV, and a cover letter.
After initial application assessment, DSTI will invite applicants for further processing. Applicants should provide documents specified in either Option 1 or 2. If these are unavailable, Option 3 may be chosen.
Option 1: Transcripts and Degree Certificate
Option 2: Standardised Tests and Degree Certificate
Option 3: DSTI Online Entrance Exam and Degree Certificate
If your application advances, we’ll invite you for a 20-minute admission interview to confirm your interest, course suitability and English fluency.
Upon acceptance, you’ll receive an official admission decision via email.
DSTI – School of Engineering
Private Higher Education Institution
As a front-runner in data and AI in France, DSTI School of Engineering offers an Applied Bachelor at RNCP 6. Our Applied MSc hold RNCP 7 accreditation. Further, DSTI is recognised under the 3IA Cote d’Azur Label for extensive AI content and proudly possesses Qualiopi RNQ certification, affirming quality of processes (download Qualiopi certificate).
DSTI School of Engineering has formed strategic partnerships and affiliations with a number of key organisations, including the likes of AWS, SAS, Microsoft, Arts et Métiers, and 3IA Côte d’Azur. These partnerships are vital because they help keep our syllabus current and our resources updated. With these partners, we are better equipped to support our students as they advance their careers in data.
950 Route des Colles
Les Templiers
06410 Biot (Sophia Antipolis)
Alpes-Maritimes, France
4 Rue de la Collégiale
75005 Paris
Île-de-France, France
+33 (0) 489 412 944
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At DSTI, we provide one-on-one online meetings with prospective students. Here we answer all their questions regarding our Applied Bachelors and Applied MSc courses.
At DSTI, we organize online group meetings where we share valuable information about our selection of Applied Bachelors and Applied MSc courses in data and AI.
DSTI organizes online group meetings to provide information about our range of Applied Bachelor and Applied MSc programs in data and AI.
Every Wednesday from 2PM to 6PM CEST, DSTI’s Paris Campus hosts an open day for all, no appointment necessary. Inquiries regarding admission, courses or other related topics are welcomed. We are delighted to provide answers to your questions.
| Fees are valid for the Autumn 24 and Spring 25 intake. | Applied MSc in Data Analytics | Applied MSc in Data Engineering for Artificial Intelligence | Applied MSc in Data Science & Artificial Intelligence | Applied MSc in Cyber Security |
|---|---|---|---|---|
| Total Tuition Fees | 18,700€ | 18,700€ | 18,700€ | 25,000€ |
| Yearly Tuition Fees | 9,350€ | 9,350€ | 9,350€ | 12,500€ |
*No tuition fees for the students in apprenticeship mode.
| Fees are valid for the Autumn 24 and Spring 25 intake. | Executive MSc in Artificial Intelligence |
|---|---|
| Total Tuition Fees | 18,700€ |
Want a career in data and AI? Download the DSTI’s Applied MSc in Data Analytics Curriculum to find out how!
