Overview
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
Educational objectives
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.
Career prospects
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.
This master is a research master and students are strongly encouraged to a PhD after the master. 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.
Institutional partners
- ENSTA Paris
- École Polytechnique
- Télécom Paris
- Télécom SudParis
Each course of the program takes place in exactly one of these schools, all schools offer at least one course of the program, and all schools are located at the same campus in the city of Palaiseau in France, just south of Paris. The final diploma will be delivered by Institut Polytechnique de Paris.
Admissions
Following our program requires a solid background in both math and CS with a good knowledge of at least one programming language. While a bachelor in math or computer science is highly recommended, we are open to diverse profiles as long as they can demonstrate their knowledge of math and computer science.
As courses are in English, the applicants need to demonstrate their capacity to follow a course in English. We don't require a specific certificate or a specific grade but the candidate are encouraged to include a test (e.g. IELTS, TOEFL), be native speakers or have followed previous programs in English.
More information and the technical information to apply are available on the official IP Paris webpage for the the M1 and for the the M2.
If you have more questions you can contact Louis Jachiet & Goran Frehse at the address master_CS_Data-Artificial-Intelligence