Online Executive MBA in Managament and Data Science
Description of the Executive MBA
This 100% Online Executive MBA in Management and Data Science offers support in the development of data science projects for managers, with no technical prerequisites.
The Executive MBA Management and Data Science is aimed at :
- working professionals or those in transition who wish to acquire the cross-disciplinary skills needed to manage data science projects; Data Science project managers (MOA);
- Managers in large companies who will be required to create and manage Data Science transformation programmes, or teams of data scientists;
- practising managers, in functional or cross-functional positions, unit managers, consultants, auditors, business unit managers and also managers of SMEs and VSEs wishing to change direction in the data science field.
Multiple awards for training
Graduates are awarded :
- the Master's degree in Business Management and Administration awarded by the University of Paris 1 Panthéon-Sorbonne;
- the MBA awarded by IAE Paris-Sorbonne;
- the MBA in Management and Data Science from ESLSCA Business School Paris;
- the Data Analyst certificate awarded by ESLSCA Business School Paris.
Why take the Executive MBA in Management and Data Science?
• A recognised degree course
Our Executive MBA Management and Data Science students will receive a Master's degree in Management and Business Administration from the University of Paris 1 Panthéon-Sorbonne - a national diploma accredited and recognised by the French State, registered in the RNCP (Répertoire national des certifications professionnelles), an MBA from IAE Paris-Sorbonne, and a Data Analyst certificate from ESLSCA, eligible for the CPF (Compte Personnel de Formation) and listed in Datadock.
• Flexible organisation compatible with your professional activity
The course is delivered part-time, in the evening, online, over 12 months, so that you can combine the course with your professional activity at a pace that suits you.
• Knowledge based on research into current management issues
The aim is to train professionals capable of meeting the challenges of the future, thanks to the expertise of our teacher-researchers in the IAE Paris Sorbonne research laboratory.
• Small group sizes to facilitate skills development, interactivity and group work
Each year there are around thirty students who benefit from classes and exchanges in small tutorial groups (4-5 students), and an online sharing platform for exchanging teaching documents and assignments.
• Teaching rooted in business practice, combining academic and professional expertise
At IAE Paris-Sorbonne, the teaching staff is made up of top-level academics and experienced professionals who are recognised experts in their fields. In addition to the Executive MBA Management and Data Sience courses, the IAE Paris-Sorbonne's professional clubs regularly bring together students and graduates from all over the world for conferences on topical subjects to identify the latest trends in data science and auditing.
• An active network of over 38,000 graduates to help you develop your career
The IAE Paris-Alumni association organises more than 150 events a year and runs around twenty professional clubs to encourage networking.
- Managerial: integrating digital into internal processes, managing and understanding in the age of data science (massive data bases, massive data collection, massive analysis)
- Technical: learning about data science (understanding, being able to use no-code tools)
- Scientific: analysing data using statistical and IT tools
Executive MBA 2024/2025 programme
- Foundations of information systems;
- The new strategic uses of data and associated technologies (Cloud, AI, IoT, Blockchain, etc);
- Digital strategy and transformation;
- Introduction to development logic (describing, structuring, exchanging and displaying data).
- From business model to strategic choices: the quest for performance in today's world;
- Lean & 6 Sigma;
- Lean startup;
- Design Thinking and open innovation;
- Managing innovative projects;
- The role of data and the digitalisation of start-ups.
- Optimising performance by managing risks and legal instruments;
- Competition, corporate governance and regulation;
- Data protection and compliance.
- Master the basics of programming with Python ;
- Use cases involving the processing, visualisation and modelling of financial data.
- Reading the financial statements;
- Measuring and steering performance;
- Financial analysis and diagnosis;
- Case studies developing the digital aspect of each subject: for example, dematerialisation, auditing and analysis of accounting data, blockchain in finance, means of payment, fintech and financial regulation, etc.
- Understanding the big data ecosystem;
- Learn about NoSQL databases;
- Carrying out a multidimensional analysis in the context of big data.
- People at the heart of management;
- Operational marketing at the service of marketing performance;
- Case studies developing the digital aspect of each subject: for example, the transformation of work and social innovation, the digital workplace, digital marketing and its tools.
- Comprendre le machine learning ;
- Mettre en œuvre des algorithmes sur un jeu de données ;
- Appliquer les modèles hiérarchiques du Deep Learning à un cas professionnel.
- Ethical and security issues related to massive data collection;
- Theory and practice of massive data collection and analysis;
- Scraping project using a crawler.
- Introduction to R;
- Fundamentals of data analysis;
- Bivariate statistics and construction of indicators;
- Statistical tests and regression techniques.
- Unsupervised exploratory analysis;
- Cluster analysis;
- Text mining;
- Dissertation methodology ;
- Supervised project;
- Project defence (in English or French).
The dissertation may be written in English or French, but must include a detailed summary in English.
The course ends with the writing of a dissertation, consisting of a project using the techniques studied in class. This will be defended orally before a jury of academics and professionals.