Objectif
Regarding the objectives of this Master, here is the link to consult
https://dataai.jachiet.com/
The master’s program will equip students with the fundamental knowledge, technical skills and concrete applied methodologies for making machines more intelligent. In particular, students will acquire experience in using and developing data-supported smart services and tools for data-driven decision making and will learn how to master technical and scientific challenges in processing large data and knowledge. The students will be taught to solve theoretical problems as well as applied ones, to present their work both in oral presentations and in written reports, to analyze the bibliography and identify open research directions, to work independently as well as in a team, to identify and seek appropriate resources for advancing their work, whether theoretical or applied, and to take initiatives.
domaines d'enseignement
Informatique.compétences acquises
Regarding the aims of this Master, here is the link to consult
https://dataai.jachiet.com/
The combination of big data and artificial intelligence in all of its forms is an active field of research. Students will be prepared for research in Robotics, Image processing, Machine Learning, Web technologies, the Social Web, Data Analytics, Big Data Management, Knowledge Base Management, Information Extraction, Information Retrieval, Databases, Data Warehousing, Knowledge Representation, and Distributed Data Management. Students who wish to pursue a PhD afterwards are more than encouraged to do that. The Institut Polytechnique de Paris and the associated research labs (INRIA, CNRS, etc.) offer a great environment for a PhD, and our program is an optimal preparation for this path. The program will also allow students to apply to positions in the industry, mostly in research and development labs.
Parcours
- DATA AI-M1 Data & Artificial Intelligence - Master 1
- 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
- FLES-MUTUALISE FLES-MUTUALISE
- Choix DATAAI BASICS Choix de cours dans le block DATAAI Basics
- DATA AI-M2 Data & Artificial Intelligence - Master 2
- Choix de cours SOFTSKILLS Choix de cours dans le bloc Softskills
- TPT-DATAAI941 Softskills seminar
- 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 M2 DATAAI Projets M2 DATAAI
- TPT-DATAAI970 Project A
- Crédits libres M2 DATAAI 5 Crédits libres M2 DATAAI
- ANG-T-209 Academic Writing
- TSP-CSC5004 Cloud Infrastructures
- TSIA201 Représentations des signaux
- IMA201(b) Introduction au traitement des images (partie b)
- TSP-CSC5003-1 Big Data Infrastructures
- ENSTA-IA302 Constraint Programming
- X-INF564 Compilation
- X-INF573 Image & Computer Vision
- X-INF562 Computational Geometry
- X-INF585 Computer Animation
- ESP-A1 Espagnol général niveau A1
- ANG-T-266 The Hobbit
- IMA204 Imagerie médicale et biologique / Représentation des connaissances S1P2 B1
- X-BIO557 Neurosciences
- IMA201(a) Introduction au traitement des images (partie a)
- IA323 Deep learning based computer vision (ROB313)
- DROIT-TECH Droit des technologies de l'information et de la communication
- IA306 Deep learning I
- DS-télécom-1 (DATA902) Optimisation pour Data Science
- IA326 Kernel Machines
- ALL-B1 Allemand général niveau B1
- IMA205 Apprentissage pour l'image et la reconnaissance d'objets
- Stages M2 Stages M2
- STGM2-IPP Stage de Master 2 IP Paris
- Choix de cours SOFTSKILLS Choix de cours dans le bloc Softskills
