LESSAC
Laboratoire d'Expérimentation en Sciences Sociales et Analyse des Comportements
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Data Science track

A new track in Data Science is available for our students!

If YOU WANT TO MANAGE DATA AND INFLUENCE BEHAVIOR, this track is for you.

This track is available over the 3 years and culminates with the MSc in Data Science and Organizational Behavior.

FIRST YEAR

Compulsory Classes: Organizational Behavior (in the experimental lab), Statistics and Data Processing, IT Tools.

Optional Classes: Game Theory, VBA Programming, Databases (second term).

SECOND YEAR

First term: Big Data and Organizational Issues

Second term: Experimental Virtual Organizations, Data Science, Business and Artificial Intelligence

MSc YEar (3rd YEAR):

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.

 

Structure of the Msc:

The MSc in Data Science and Organizational Behavior intends to train future leaders, data scientists and academics to the management of big data and behavioral change to a high level of expertise.

The specificity of the program relies in the intersection between management, behavioral tools and rigorous understanding of the managerial and economic issues contained in the data.

The program:

i)                    offers students a unique program and advanced knowledge in behavioral and data sciences;

ii)                   is taught by scientists, researchers and corporate partners in complete connection with their own activities in the field.

Objectives:

Core Courses:

i)                    key concepts, models and advanced tools of behavioral and experimental economics;

ii)                   advanced models and modern statistical algorithms in data science;

iii)                 applications to decision making in management and development of organizational tools within organizations, business policy, strategy and policymaking;

Concentration Courses:

i)                    the business of information: creating value and using information to modulate behavior;

ii)                   technological perspectives and the relation with Information Systems Management and Information Communication Technologies at the workplace in activities such as planning and performance monitoring;

iii)                 data analytics and the consequences of ICT use on employees, leaders and organizations;

iv)                 (de)centralization and its impact on the structure of decision-making;

v)                  the role of Big Data and digital management strategy on motivation and productivity in the workplace.

The Master thesis is a supervised laboratory practice-oriented project in partnership with a company.

A "field" trip is organized every year.

Target Skills:

Creating value from information. The power of (big) data. Statitics and Data analytics. Understanding how data can be used to make business. 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.

Target jobs:

We form experts with a unique knowledge in the intersection between management, data science and behavior, able to put in practice effective tools to understand and modify decision making and deal with big data in organizations and with the behavioral implications of AI. 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): MGE 3 Core courses and MSc core courses

2nd term (Spring) : MSc advanced courses

3rd term (summer) : professional thesis and internship (if applicable)

Modules :

Block 1: Data Management (160 contact hours)

Autumn modules (1st term, in addition to common MGE modules) :

Module 1 : Data Science Methods

40 h

Description: Introduction to computer sciences applied to data management.

Objectives: Learning the basics of Structured programming and languages such as VBA or Python.

Module 2 : Applied Information Analysis

40 h

Description: Statistics and qualitative tools for managing and analyzing new data sets (e.g. text messages, images, videos..)

Objectives: Using latest packages for data analysis (e.g. R, Stata, Text Visualisation).

Spring Modules (2nd term) :

Module 3 : Recent Topics in Data Science

40 h

Description: Advanced topics in Programming dealing with data management.

Objectives: Understanding the main concepts of Machine Learning, Object oriented programming, Mobile Apps Creation, etc.

Module 4 : Big Data Practical Applications

40 h

Description: In this module several professionals in data management will present successul applications of Big Data, from the idea to the business.

Objectives: Indentify, assess and develop big data business models.

Block 2: Behavioral Sciences (160 contact hours)

Autumn modules (1st term, in addition to common MGE modules) :

Module 5 : Behavioral Methods & Applications

40 h

Description: introduction to experimental methods and games fundamentals for the analysis of humans behavior.

Objectives: Understanding the basics of experimental studies in behavioral sciences.

Module 6 : Behavioral Tools

40 h

Description: designing and developing decision making and behavioral economics experiments.

Objectives : Being able to create your own behavioral scenario using Ztree, Otree, …

Spring Modules (2nd term) :

Module 7 : Behavior in Organizations and Markets

40 h

Description: study of human behavior in organizations and markets and how insights from behavioral sciences can help managers to make better decisions.

Objectives: Understanding how human behavior can be shaped.

Using simulated scenarios (e.g. Virtual Organizations, Financial Markets, Personal Markets) to study human behavior.

Module 8 : Behavioral Strategies for Business and Management

40h

Description: At the intersection of data science and behavioral sciences, this module analyzes several applications of behavioral techniques into business. How can we make money understanding behavior?

Objectives: evaluate business needs, design and develop field interventions on specific industry problems.

Block 3: Professional supervised thesis (80 contact hours)

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.

All informations are available here.

 



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