Program Overview

Introduction to the Master MIND Program

The Master MIND program at Sorbonne Université focuses on artificial intelligence, learning, and data science. Previously known as the DAC program, it aims to equip students with fundamental knowledge in computer science and statistics, as well as mastery of associated information technologies.

Objectives

The pedagogical objective of the Master MIND program is to provide students with comprehensive knowledge in all domains of artificial intelligence centered on data usage, knowledge production, and the implementation of intelligent services. This includes:

• Database management for collecting, storing, and querying large amounts of complex data
• Machine learning to extract statistical and symbolic models from imperfect data
• Computational intelligence to reason and exploit knowledge extracted from data

Career Prospects

The Master MIND program prepares students for careers as designers, developers, and users of intelligent tools in various domains requiring strong data treatment, analysis, and enrichment skills. Potential career paths include:

• Researcher in AI, developer of deep learning architectures for text, image, or signal data
• Web management, web advertising, design of social platforms
• Business Intelligence, Customer Relationship Management (CRM)
• Information retrieval and search engines on the web and social platforms
• Database tuning, data analyst, data architect, data engineer, data manager on distributed architectures

Program Structure

The first semester of the M1 program offers a common core with other computer science tracks, including mandatory and highly recommended courses that introduce:

• Models and languages for storing and accessing structured and semantic data
• Fundamental tools and best practices in data science and machine learning
• Knowledge representation and management
• Probabilistic approaches for data analysis

From the second semester of the M1 onwards, the program offers three competency profiles:

• The "Apprentissage" (Learning) profile, focusing on machine learning, deep learning, and applications in information retrieval and natural language processing
• The "Bases de Données" (Database) profile, focusing on database management for complex and distributed data
• The "Intelligence Artificielle" (Artificial Intelligence) profile, focusing on knowledge modeling and symbolic learning for complex and uncertain information

Competencies Acquired

Upon completion of the program, graduates will master:

• The challenges, issues, and context of large-scale information processing
• Basic AI tools
• Symbolic and numerical technologies for machine learning from data
• Basic tools for information retrieval
• Components of an operational data mining tool
• The functioning of search engines for text, image, speech, and video

Graduates will also be able to implement and innovate in the design of:

• Large-scale data management, collection, and analysis systems
• Data mining tools, information retrieval, and technological watch
• Machine learning algorithms and pattern recognition

Target Audience and Prerequisites

The program is primarily aimed at students with a background in computer science or computer science/mathematics at the L3 level (or equivalent). Motivated candidates from other scientific fields may also be considered. For the M2 level, the program can accommodate external candidates with compatible prerequisites, particularly students from engineering schools seeking a double degree.

Candidates must have solid knowledge in computer science (algorithms, programming, databases, logic) and fundamental mathematics (probability, statistics). The Master MIND program is not offered in an alternating format due to the requirement for foundational courses, especially in the M1 semester.