Descriptif
The DataAI study track is a two-year master’s program at the Institut Polytechnique de Paris to prepare students for a PhD. It is concerned with Artificial Intelligence (AI) and large-scale data management. To apply, you can browse the official IP Paris webpage for the the M1 and for the the M2.
The program is taught in English. It teaches students the basics of Machine Learning, Logic, Big Data Systems, and Databases, before diving into applications in advanced machine learning, symbolic AI, swarm intelligence, natural language processing, visual computing, and robotics. Students can choose from a wide variety of courses, including on the mining of large datasets, big data processing systems, reinforcement learning, GPU programming, semantic networks, cognitive modeling, self-organizing multi-agent systems, autonomous navigation for robots, text mining, image understanding, as well as social issues in AI.
The program has a focus on research, and aims to familiarize students from the beginning with scientific work with scientific projects and internships. This way, students are optimally prepared for doing a PhD.
- Language of instruction: English
- ECTS: 120
- Orientation: PhD
- Duration: 1 year (M2) or 2 years (M1+M2)
- Start: September
- Course Location: Quartier Polytechnique, Palaiseau, France
Diplômes concernés
Composition du parcours
- Choix DATAAI BASICS Choix de cours dans le block DATAAI Basics
- TPT-DATAAI900 DATA AI BASICS
- Choix de cours ETHICS Choix de cours dans le bloc Ethics
- TPT-DATAAI951 AI Ethics
- Choix de cours LOGICS Choix de cours dans le bloc Logics
- Choix BIG DATA SYSTEMS Choix de cours dans le bloc Big Data Systems
- X-INF583 Systems for Big Data
- TPT-DATAAI921 Architecture for Big Data
- CSC5003 Infrastructures d'analyse de données
- Choix de cours DATABASES Choix de cours dans le bloc Databases
- X-INF553 Database Management Systems
- SD202 Databases / Bases de données
- SD202 (cr.D) Databases (créneau D)
- Choix FULLY OPTIONAL COURSES Choix de cours dans le bloc Fully Optional Course
- IA317 Machine learning in high dimension
- IA327 Sequence-to-Sequence Models for NLP and Speech Processing
- TP09 Social Emergence in Complex Systems (Télécom Paris - Palaiseau)
- SD201 Exploration de données
- IA307 Programming with GPU for Deep Learning
- SD212 Graph Learning
- IA312 Natural Language Processing
- DATAAI966 Multimodal Dialogue
- IA318 Reinforcement learning
- X-INF657G Navigation for autonomous systems
- IA304 Modèles probabilistes et apprentissage automatique
- X-INF581-1 Advanced Machine Learning and Autonomus Agents
- X-INF556 Topological Data Analysis
- X-INF582 Text Mining and NLP
- X-INF641 Introduction to the verification of neural networks
- X-INF552 Data Visualization
- TPT-DATAAI903 Image mining and content-based retrieval
- TPT-DATAAI902 Explainable and Trustworthy AI
- TPT-DATAAI961 Self-organising multi-agent systems
- TPT-DATAAI964 Knowledge Base Construction
- TPT-DATAAI968 Deep Learning for Computer Vision
- TPT-DATAAI969 Representation Learning for Computer Vision and Medical Imaging
- X-INF581A Advanced Deep Learning
- ENSTA-INF656L Decision Procedures for Artificial Intelligence
- MAP654I Practical introduction to machine learning
- Projets M1 DATAAI Projets M1 DATAAI
- Crédits libres M1 DATAAI 5 crédits libres à choisir en M1 DATAAI
- IA713 Algorithmique des procédures de décisions en logiques et contraintes
- LSF-A1 Langue des signes française
- FLES-MUTUALISE FLES-MUTUALISE
- X-LAN576FLE Cours de langue
- SES210 Sociologie du numérique
- TSP-CSC5003-1 Big Data Infrastructures
- ENSTA-IA302 Constraint Programming
- X-BIO557 Neurosciences
- IGR204 Visualisation
- Stages M1 - Stages M1 DATAAI
- Stages PhD Track M1 - Stages PhD Track M1
