MSc DSOB
Our Msc in Data Science and Organizational Behavior is available for our students, in partnership with PWC Luxembourg!
See our short video about here, and another here.
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Our students with Vernon Smith (Nobe Prize en Economics)
at the Organizations and Markets Workshop in 2018.
If YOU WANT TO MANAGE DATA AND INFLUENCE BEHAVIOR, this MSc is for you.
To train future leaders and academics in data and behavior management to a high level of expertise in the intersection between management, behavioral tools and data science.
The programme is created to give students programming skills, both by syntax (IT tools) and module (games tools), which is a unique way of teaching the subject.
Our scientific and professionnal partner on this MSc in PriceWaterhouseCooper Luxembourg.
See here the press release about our partnership.
« Aujourd’hui plus que jamais, la donnée est sur toutes les lèvres et pousse les parties prenantes de notre société à se réinventer », explique Vincent Ball, associé chez PwC Luxembourg. « Nos métiers sont en pleine mutation afin de s’adapter à cette nouvelle ère. Notre firme est avant tout connue pour ses qualités et son réseau d’audit, mais les métiers de notre branche Conseil et Stratégie viennent compléter une large gamme de services aux entreprises afin de répondre aux différentes demandes de nos clients. »
« Ce partenariat va permettre aux étudiants de traiter un certain nombre de problématiques internes à notre organisation mais aussi d’envisager certaines études de cas concrets sur le modèle de ce qui est proposé à nos clients, et dont les recommandations prédictives seront présentées en situation réelle de clientèle, tout en espérant voir certains étudiants nous rejoindre à l’issue de leur MSc », ajoute Vincent Ball.
MSc Data Science and Organisational Behaviour (MSc DSOB)
MSc Data Science and Organisational Behaviour (MSc DSOB)
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MSc Data Science and Organisational Behaviour |
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Department: |
Economie et Sciences Sociales |
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Specialisation's Managers: |
Angela Sutan Frank Lentz |
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Minimum number of places: |
15 |
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Maximum number of places: |
40 |
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Structure: The MSc in Data Science and Organisational Behaviour intends to train future leaders, data scientists and academics to the management of big data and behavioural change to a high level of expertise. The specificity of the program relies in the rigorous understanding of the intersection between data management and behavioural tools. The program: i) offers students a unique program and advanced knowledge in behavioural and data sciences; ii) is taught by scientists, researchers and corporate partners in complete connection with their own activities in the field. This program is taught and defined in partnership with PWC Luxembourg. |
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Admission requirements:
Admission process:
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Professional skills: Creating value from information. The power of (big) data. Statistics and Data analytics. Understanding how data can be used to make business and influence decisions. Communication with data users. Data representation. Data transformation and analysis for decision makers. Ethical reasoning. Reduce, sample, create analytics, summarize information, present it in a useful way to the decision maker and make a set of scattered data something useful for users of them. |
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Career perspectives: We form experts with a unique knowledge in the intersection between management, data science and behaviour, able to put in practice effective tools to understand and modify decision making and deal with big data in organizations. We form professionals with a strong and useful research background likely to act in functions such as data analysts, data scientists, global strategists, analysts in counselling companies, chiefs in marketing services, management consultants, government officials, economists in banks and financial organizations, human resources managers etc… or develop their own company. Most of our students work at PWC Luxembourg, but also at M6, Olympique Lyonnais, Etablissement Français du Sang etc... |
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Structure:
1st term (Autumn): 2 blocks of study, Data Management and Behavioral Sciences 2nd term (Spring): 2 blocks of study, Data Management and Behavioral Sciences, advanced. 3rd term (summer): professional thesis and internship (if applicable). Field trips : one at Marché du Brionnais and one (3 days) at PWC Luxembourg (scroll for all pictures). Our students also participate in scientific seminars and experimental economics conferences (see here ESA 2019 and ASFEE 2021 - scroll for all pictures) In addition preparatory data camps will be provided to you before the classes start. |
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CURRICULUM |
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Block 1: Data Management (200 contact hours) |
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Autumn modules (1st term): |
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Module 1: Data Science Methods (intermediate) Contact hours: 42 h |
Outline: Introduction to Data Sciences languages (R and Python) for data wrangling and analysis Learning goals:
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Module 2: Sql and data bases Contact hours: 18 h |
Outline: Databases conception and Data manipulation Learning goals:
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Module 3: Business-Oriented Data Governance Contact hours: 18 h |
Outline: Organization and Data Governance, data ownership, data steward, NLP, data cleaning, (VBA), customer intelligence Learning Goals:
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Module 4: Data General Knowledge Contact hours: 18 h
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Module 5: Seminars Series & Partner Class 1 Contact hours: 30 h |
Classes by our partners (PWC Luxembourg, ...) and invited researchers and Case studies on real business cases The topics change every year Examples of topics:
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Spring Modules (2nd term): |
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Module 6: Recent Topics in Data Science Contact hours: 42 h |
Outline: Introduction to machine learning and Neural Networks Learning goals:
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Module 7: Data Science Methods (Advanced) Applications Contact hours: 42 h
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Outline: Advance topics in data science and BI Learning goals:
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Module 8: DS - Seminars Series & Partner Class 2 Contact hours: 51 h
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Classes by our partners (PWC Luxembourg, ...) and invited researchers and Case studies on real business cases The topics change every year Examples of topics:
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Block 2: Behavioural Sciences (198 contact hours) |
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Autumn modules (1st term): |
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Module 9: Applied Information Analysis (intermediate) Contact hours: 42 h
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Outline: Statistics with R applied to OB cases Learning goals:
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Module 10: Behavioural Tools Contact hours: 42 h |
Outline: designing and developing decision making and behavioural economics experiments. Learning goals:
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Module 11: Behavioral Decision Making and Communication Contact hours: 18
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Outline: Influence tools, nudges, experimental designs, AI ethics, human vs. machine intelligence, singularity, project chief simulations, root cause analysis (RCA), feedback Learning goals: Learn to design interventions in companies, work on real use cases from partners. |
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Module 12: Entreprise et réalités (Firm and realities) Contact hours: 12
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Common class with the general school program on real situations acting. |
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Spring Modules (2nd term): |
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Module 13: Behavioural Strategies for Business and Management Contact hours: 42 h |
Outline: At the intersection of data science and behavioural sciences, this module analyses several applications of behavioural techniques into business. How can we make money understanding behaviour? Learning goals:
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Module 14: Applied Information Analysis 2 (Advanced) Contact hours: 42 h
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Outline: Statistics and econometrics applied to OB Learning goals:
Tools:
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Block 3: Professional supervised thesis |
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Module 15: Research Methodology Contact hours: 16 The specificity of the professional thesis in the MSc is that this is a project lead in the lab, under close and permanent supervision for programming, design and tests, in close coordination with a company. The sequence and requirements of this module follow the general program stream, using specific data tools. |
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