Master SID-Big data

The SID programme is a training resolutely geared towards the data engineering professions. It covers all aspects of it: from data collection to statistical exploitation and machine learning, including the storage and management of massive big data databases. It takes place over 3 years from License 3 to Master 2, with a progressive learning of fundamental concepts, methodologies and tools used in data science. In the age of artificial intelligence, the “data scientist” profile of SID students is enhanced by a dual statistical competence - business intelligence, with a specialization in machine learning and databases. This type of profile is highly demanded in various professional fields today, as shown by the 100% hiring rate of our students upon graduation from Master 2. Some examples of projects and internships:

• Projet de Master 1 : Data, text et web mining
• Projet de Master 2 : Challenge big data
• Projet inter-promo L3-M1-M2
• Stages de Master 1 et Master 2

The M2 SID is the last year of the SID training. Students can register for initial training or work-study:

• Work-study contract: One-year professionalization or apprenticeship contract (from September to September) divided into 17 weeks at the university and 34 weeks in a company (according to the schedule established in advance).
• In initial training: At the university from September to mid-March (with projects), then internship until the end of August. More information in the frame on work-study.

The vast majority of M1 SID students (respectively M2 SID) come from a degree in mathematics, computer science or data science. Candidates wishing to integrate the Master SID must submit an application on Monmaster.gouv.fr for the first year and ecandidat for the second year.
 More details available from this page: http://www.univ-tlse3.fr/candidatures/

• Work-study contract? The work-study contract is possible for the two years of Master or only for the second year.
• Distance training? We do not offer distance training. We consider the face-to-face teaching as very important for the smooth running of the training, in particular for practical work and projects.
• Number of students? Between 35 and 40 students per year of the Master. This reasonable size promotes the spirit of promotion and mutual knowledge of all students in the course (L3, M1 and M2).
• Internship in M1? The duration of the internship varies from a minimum of 3 months to a maximum of 5 months. Information will be given to you at the beginning of the year to help you in your search for an internship.
• Why choose the SID course at Paul Sabatier University? Become a data scientist at Bac + 5 with expert and innovative skills A teaching program in perfect harmony with the needs of the market (100% hiring rate after leaving M2 SID). A training recognized by many professional partners, forming a substantial network to find internships, work-study programs and positions. Very good supervision thanks to a dedicated teaching team.
• Can a sports score be counted in SID? No, but the schedule leaves the possibility of exercising a sporting activity.

• Implement a statistical study from planning to analysis and synthesis of results (Survey, Marketing, Biomedical study, Statistical Process Control).
• Design and develop an information system (relational database or NoSQL) to support the functioning of an organization.
• Extract relevant information from textual or structured data sources in order to enhance them (decision support, information research, data mining) in a company, in an administration, or in a research environment.
• Analyze massive amounts of data and build dashboards for the management of institutions (companies, administration, etc.)
• Maintain and analyze a decision-making system (data warehouse, OLAP, ERP) to manage the resources of an organization
• Work in a team by following project management methodologies
• Exchange and express yourself easily orally and in writing in French and English, in a professional context
• Build and validate a mathematical model to process data sets (from surveys, surveys, sensors, etc.), in order to develop decision support tools in a business, in an administration, or in a business environment research.