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Laboratoire d'Expérimentation en Sciences Sociales et Analyse des Comportements
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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, another video here and a longer one here.

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)

 

MSc Data Science and Organisational Behaviour

Department:

Economie et Sciences Sociales

Specialisation's Managers:

Angela Sutan

Frank Lentz

Email: angela.sutan@bsb-education.com

Minimum number of places:

15

Maximum number of places:

40

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.

Admission requirements:

  • English language certificate (for non-native speakers): TOEIC (785), IELTS (6.5)

 

Admission process:

  • Please contact the Head of Programme (angela.sutan@bsb-education.com) for interview after submitting application. You will be required to pass a test and you will be called to an interview.

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.

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.

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).

 

CURRICULUM

Block 1: Data Management (200 contact hours)

Autumn modules (1st term):

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:

  • Master the basics of R and Python
  • Master the libraries for data wrangling and cleaning
  • Produce basic analysis

 

Module 2: Sql and data bases

Contact hours: 18 h

Outline: Databases conception and Data manipulation

Learning goals:

  • Understand the structure of databases
  • Master DDL, DML and DCL
  • To be able to create and populate a database in the context of a Data Science project

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:

  • To be able to conduct a reflection on the governance of a company
  • Using data governance for effective governance

 

Module 4: Data General Knowledge

Contact hours: 18 h

  • To identify the different types of data
  • To understand the organisation of data in a business
  • To understand the management of data in the data science process and identify the related technologies and practices
  • IOT, cloud, MDM/RDM, ETL, Data, Talend, DataPrep,  data minimization, ERP, CRM, business for worth, SAP, business objects, reporting, dashboard, user experience...

 

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:

  • Information systems audit
  • Big Data Tools
  • Data visualisation
  • Data analytics in sports
  • Fraud Detection
  • Market Basket Analysis
  • Spatial Analysis
  • Data Management
  • Social Network Analysis
  • ...

Spring Modules (2nd term):

Module 6: Recent Topics in Data Science

Contact hours: 42 h

Outline: Introduction to machine learning and Neural Networks

Learning goals:

  • Understand the main machine learning algorithms
  • Select an algorithm correctly according to the business case
  • Be able to use the main machine learning algorithms with R Python or MatLab
  • Have an understanding of neural networks and their applications

 

Module 7: Data Science Methods (Advanced) Applications

Contact hours: 42 h

Outline: Advance topics in data science and BI

Learning goals:

  • To be able to implement interactive dashboards (R Shiny, PowerBI or Tableau, Alterix)
  • Text mining (R or Python)

Module 8: DS - Seminars Series & Partner Class 2

Contact hours: 51 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:

  • Information systems audit
  • Big Data Tools
  • Data visualisation
  • Data analytics in sports
  • Fraud Detection
  • Market Basket Analysis
  • Spatial Analysis
  • Data Management
  • Social Network Analysis
  • ...

Block 2: Behavioural Sciences (198 contact hours)

Autumn modules (1st term):

Module 9: Applied Information Analysis (intermediate)

Contact hours: 42 h

Outline: Statistics with R applied to OB cases

Learning goals:

  • Descriptive statistics
  • Parametric tests
  • Non Parametric tests
  • ANOVA
  • Linear Regression

 

Module 10: Behavioural Tools

Contact hours: 42 h

Outline: designing and developing decision making and behavioural economics experiments.

Learning goals:

  • Being able to create your own behavioural scenario using Ztree, Otree, …
  • Master the basis of python to code experiments

 

Module 11: Behavioral Decision Making and Communication

Contact hours: 18

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.

Module 12: Entreprise et réalités

(Firm and realities)

Contact hours: 12

Common class with the general school program on real situations acting.

Spring Modules (2nd term):

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:

  • evaluate business needs, design and develop field interventions on specific industry problems.
  • To be able to analyse Social and economic networks
  • To be able to analyse structured and unstructured data

 

Module 14: Applied Information Analysis 2 (Advanced)

Contact hours: 42 h

Outline: Statistics and econometrics applied to OB

Learning goals:

  • Time series and financial data analysis
  • Probit
  • Logit
  • Bayesian Statistics

Tools:

  • R, Gretel, Matlab ….

Block 3: Professional supervised thesis

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.

 

 

All informations are available here.





If you want to enroll, please contact:
angela.sutan@bsb-education.com