DATA Minor
Université PSL is developing minors on a range of particularly interesting topics, closely linked to scientific and socioeconomic challenges. This represents a chance to enroll in advanced courses on topical issues, and, for PhD students, to contribute to your research by addressing new topics and new tools. These new minors offer unprecedented opportunities for Université PSL students in Master’s degrees and Doctorates from all our component schools.
Openness and specialization with Université PSL minors
At Université PSL, a minor is validated in parallel with a major (Master’s degree or Doctorate) and can be spread over several years (subject to registration at Université PSL). The minor is validated following the meeting of a jury, with a certificate awarded confirming the volume of learning, which represents thirty ECTS credits (i.e., the equivalent of one semester of a Master’s degree).
DATA Minor to certify your skill level in AI & Data Science
The DATA minor is available to all students of Université PSL. On completion, a certificate is awarded certifying a level of competence in AI and Data Science adapted to their original discipline.
The DATA program brings together all training in AI and Data Science offered at Université PSL for students to develop cutting-edge skills in data analysis, and to give them a better understanding of the challenges of the digital world. To obtain this certificate, select the appropriate courses from among the many classes and training opportunities available in the DATA program.
To obtain this minor, at least 30 ECTS credits are needed during the Master’s degree and/or Doctorate, in one of three ways :
1. Validation of prior learnings and experience
Students who have already followed courses or validated their experience in the field of DATA science may compile a file with the following supporting documents: syllabus of the course in question and proof of validation showing the number of associated ECTS credits and the number of hours. This application will be submitted to the assessment jury for the DATA program which will decide whether some or all of this experience is validated.
2. Training courses offered in the DATA program
Students have the possibility of validating their minor by choosing courses from amongst those offered as part of the DATA Program (Preparatory weeks, PSL weeks, Hackathons, etc.). See details below.
NB: The two dedicated preparatory weeks proposed by the DATA program are a precondition for the certificate (unless the student demonstrates comparable skills as part of a previous course of study).
3. Approved DATA science courses in Université PSL graduate programs
Students have the possibility of validating their minor by following Master’s degree courses certified by the DATA program within their own study curriculum (depending on the graduate program to which they belong).
The following graduate programs offer approved DATA science courses from the 2023-4 academic year:
- Courses in the Graduate Program of Economics
- Courses in the Graduate Program of Finance
- Courses in the Graduate Program of Cognitive Sciences
- Courses in the Graduate Program of Physics
- Courses in the Graduate program of Life Sciences
- Courses in Engineering at ESPCI Paris - PSL
Students who have validated 30 ECTS as described above must compile a file that contains the following:
- A short presentation of their program (identity, course of study, school of enrollment) and a copy of their student card (or certificate of registration)
- List of courses followed or internships that may be eligible for validation for the DATA Minor
- Proof of their validation (official transcript from their school) showing the number of associated ECTS credits
This file should be sent to mineuredata@psl.eu with the subject line “Demande de validation de la mineure DATA” (Request for validation of the DATA minor). Each year, a jury meets in December, and the deadline for sending in applications is November 15 (23:59, Paris time).
NB: If the application includes courses with very similar contents, only one of these will be counted towards the 30 ECTS that must be validated. If in doubt, students can contact the head of their original study course or write to mineuredata@psl.eu.
Validation of prior learnings and experiences
Students who have already taken courses or gained skills in DATA science may compile a file that includes the following supporting documents: the syllabus of the course in question and proof of validation showing the number of associated ECTS credits and the number of hours. This application will be submitted to the assessment jury for the DATA program which will decide whether some or all of this experience is validated.
Training opportunities in AI and Data in the DATA program
Two preparatory weeks are offered. These are precontions for the certificate (unless the student demonstrates comparable skills as part of a previous course of study).
• Week 1 – Fundamentals of Mathematics and Computer Science (3 ECTS) | The basics of mathematics and computer science for data science. The week can be followed asynchronously.
• Week 2 - Machine Learning and Database (3 ECTS) | This takes place at the end of August/beginning of September on the PariSanté Campus.
The 2024 program for these 2 weeks will be published soon.
Intensive DATA weeks are PSL weeks providing scientific and technical immersion in AI, at the interface with another discipline. 2 ECTS are awarded at the end of each week.
Details of the program can be found on the PSL weeks website.
PSL weeks from 27 November 2023 to 1st December 2024:
- AI for Economics and Finance
- Explainability and Interpretability in Artificial Neural Networks
- Ethics and Artificial Intelligence
- NLP for Social Sciences
PSL weeks from 4 March 2024 to 8 March 2024:
- Digital Humanities meet Artificial Intelligence
- Machine learning for physics and engineering
- Green Artificial Intelligence
- Machine learning in Genomics
- NLP for Social Sciences
- Statistical Physics and Machine Learning
- Data mining and modeling for behavioral sciences and beyond
Hackathons (6 ECTS) give a group of students the opportunity to develop a scientific project at the interface between AI and their own discipline over a 8-week period, with technical supervision.