Master Mathématiques Appliquées, Statistique, Parcours : Data science (DS)

The Data Science course trains students to handle and manage data, visualise and analyse it. Students will be trained in applied mathematics (probabilistic, optimisation, signal and image processing, etc.), statistics and computer science (machine learning, databases, programming). The scientific and technical knowledge acquired in this course will enable them to carry out data analysis using modern methods, but also to design and analyse statistical and computer tools for prediction or decision support, to implement innovations and to manage projects within a company.

After completing this course, the graduates of this course are mainly destined to occupy Data Scientist positions, or engineer level positions in statistics, signal and image processing or machine learning.

For entry into M1, the prerequisites correspond to the skills acquired in a scientific degree with a strong mathematical content (bachelor's degree in mathematics, bachelor's degree in computer science / course in mathematics and computer science, bachelor's degree in MIASHS, bachelor's degree in MPCI, bachelor's degree in Sciences and Humanities).

• SCIENCES, Marseille St-Charles

The Data Science course is a modern multidisciplinary scientific and technical training, combining the disciplines of mathematics, statistics, signal and image processing and computer science to understand and analyse data. It has a double purpose, initiation into research and professionalization of students. It is led by a young, dynamic teaching team, composed of professionals and members of two research units: the Institut de Mathématiques de Marseille (I2M), and the Laboratoire d'Informatique et Système (LIS).

• Construct an explanatory or predictive model, through data analysis, based on a mathematical and statistical methodology.
• Design, program and implement a digital method, processing and analysis of data
• Design, program and implement a digital method of data processing and analysis, using statistical and scientific computing software. Evaluate its effectiveness.
• Design, program and implement statistical tools for decision support
• Organise and visualise a complex, possibly massive dataset to describe a dataset and represent the information it contains

A dissertation in M1, and tutored projects give an opening, including towards research. Two internships (2 months in M1 and 4-6 months in M2) are provided.

In addition to the classic university methods (lectures, tutorials, exams), this course offers numerous tutorials and practical work on the computer, in order to learn how to manipulate and visualise data, program and implement analysis methods. A dissertation in M1, and tutored projects provide an opening, including towards research. Two internships (2 months in M1 and 4-6 months in M2) are provided.

• H1206 Management et ingénierie études, recherche et développement industriel (fr)
• K2108 Enseignement supérieur (fr)
• K2402 Recherche en sciences de l'univers, de la matière et du vivant (fr)
• M1403 Études et prospectives socio-économiques (fr)

• 114B Modèles mathématiques ; Informatique mathématique (fr)
• 114C Mathématiques de la physique, de la chimie, de la biologie (fr)
• 114G Mathématiques de l'informatique, mathématiques financières, statistique de la santé (fr)