Master Year 2 Data and Artificial Intelligence
| Year | Master Year 2 |
| Program | Data and Artificial Intelligence |
| ECTS Credits | 60 |
| Language | English |
| Orientation | Research and Industry |
| Location | Palaiseau Campus |
| Course duration | 12 months, full time |
| Course start | September |
| Degree awarded | Master’s degree obtained on completion of a second year of Master |
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.
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.
For more infomation on the program you can visit : https://dataai.telecom-paris.fr/
Objectives
The Master’s program aims to enable students to:
- Acquire the fundamental knowledge, technical skills and concrete applied methodologies to make machines more intelligent
- Gain experience in using and developing data-supported smart services and tools for data-driven decision making, while exploring the technical and scientific challenges of processing large data and knowledge bases
- Solve theoretical and applied problems, present their work in oral presentations and written reports, analyze a bibliography and identify open research directions, work independently and in a team, identify and seek appropriate resources for advancing their work
Students who successfully complete the 2-year program will be equipped to:
- Build a successful research career in robotics, image processing, machine Learning, web technologies, social web, data analytics, big data management, knowledge base management, information extraction, information retrieval, databases, data warehousing, knowledge representation and distributed data management
- Pursue a PhD at Institut Polytechnique de Paris
To validate the Master Year 2, a student must accomplish the following:
- fulfill all the Data AI mandatory course requirements (see below)
- acquire a total of at least 30 ECTS courses (including the mandatory courses) with at least 25 ECTS in Data AI courses
- validate the M2 internship for 30 ECTS
Students must validate at least one course for each groups, before the end of the Master year 2 (courses completed in M1 count as validated):
You can consult the list of Data AI courses on this page.
Students should not take two courses with overlapping topics, for details see the course descriptions.
All Data AI courses are 24h, count 2.5 ECTS, and are validated by labs, presentations and/or exams. A course is validated when the student obtains a grade of 10/20 or higher.
Academic prerequisites
Completion of the first year of a Master in computer science or related field at Institut Polytechnique de Paris or equivalent in France (Engineering School) or abroad.
Language prerequisites
English: proof of English proficiency is required (TOEFL results, language course or language test), except for native speakers and students who previously studied in English.
How to apply
Applications can be submitted exclusively online. You will need to provide the following documents:
- Transcript
- Two academic references (added online directly by your referees)
- CV/resume
- Statement of purpose
You will receive an answer in your candidate space within 2 months of the closing date for the application session.
Fees and scholarships
Registration fees are available here
Find out more about scholarships
Please note that fees and scholarships may change for the following year.
Applications and admission dates
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.
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.
For more infomation on the program you can visit : https://dataai.telecom-paris.fr/
Objectives
The Master’s program aims to enable students to:
- Acquire the fundamental knowledge, technical skills and concrete applied methodologies to make machines more intelligent
- Gain experience in using and developing data-supported smart services and tools for data-driven decision making, while exploring the technical and scientific challenges of processing large data and knowledge bases
- Solve theoretical and applied problems, present their work in oral presentations and written reports, analyze a bibliography and identify open research directions, work independently and in a team, identify and seek appropriate resources for advancing their work
Students who successfully complete the 2-year program will be equipped to:
- Build a successful research career in robotics, image processing, machine Learning, web technologies, social web, data analytics, big data management, knowledge base management, information extraction, information retrieval, databases, data warehousing, knowledge representation and distributed data management
- Pursue a PhD at Institut Polytechnique de Paris
To validate the Master Year 2, a student must accomplish the following:
- fulfill all the Data AI mandatory course requirements (see below)
- acquire a total of at least 30 ECTS courses (including the mandatory courses) with at least 25 ECTS in Data AI courses
- validate the M2 internship for 30 ECTS
Students must validate at least one course for each groups, before the end of the Master year 2 (courses completed in M1 count as validated):
You can consult the list of Data AI courses on this page.
Students should not take two courses with overlapping topics, for details see the course descriptions.
All Data AI courses are 24h, count 2.5 ECTS, and are validated by labs, presentations and/or exams. A course is validated when the student obtains a grade of 10/20 or higher.
Academic prerequisites
Completion of the first year of a Master in computer science or related field at Institut Polytechnique de Paris or equivalent in France (Engineering School) or abroad.
Language prerequisites
English: proof of English proficiency is required (TOEFL results, language course or language test), except for native speakers and students who previously studied in English.
How to apply
Applications can be submitted exclusively online. You will need to provide the following documents:
- Transcript
- Two academic references (added online directly by your referees)
- CV/resume
- Statement of purpose
You will receive an answer in your candidate space within 2 months of the closing date for the application session.
Fees and scholarships
Registration fees are available here
Find out more about scholarships
Please note that fees and scholarships may change for the following year.