DATA Minor

PSL University is developing a range of minors focused on particularly compelling themes, closely aligned with contemporary scientific and socio-economic issues. Whether seeking to broaden their horizons or enhance their professional skills, commit to a path of specialisation, or enrich their research by exploring new themes or employing new tools, the minors offered by PSL University provide unique opportunities for master’s and doctoral students across all our institutions.

Specialisation with PSL University Minors

Completion of a minor at PSL University is undertaken alongside a primary programme (master’s or doctoral), and may extend over several years (subject to enrolment at PSL University). Upon the assessment by a panel, the successful completion of the minor results in the award of a certificate, recognising a learning volume equivalent to approximately thirty ECTS credits (the equivalent of one semester of a master’s programme). The validation requirements for each minor at PSL University are specified, including a set of accredited courses and eligible activities such as PSL Weeks, summer schools, internships, etc.

The Data Minor to Certify Your Level of Expertise in AI and Data Science

Offered to all students at PSL University, the Data Minor provides a certificate that validates a level of proficiency in AI and data science, tailored to the student's primary field of study.
The Data Programme integrates all training opportunities in AI and data science available at PSL University, allowing students to acquire advanced skills in data analysis and to gain a comprehensive understanding of the challenges in the digital realm. Students will fulfil the requirements for the certificate through a selection of courses and training activities within the Data Programme.

How to Undertake the Courses for the Data Minor ?

To validate this minor, it is necessary to accumulate at least 30 ECTS credits during the Master’s and/or doctoral programme, through one of the following three options:

1. Recognition of Prior Learning

Students who have previously completed courses or acquired skills in the field of Data Science may compile a portfolio with supporting documents, including the syllabus of the relevant course and proof of validation indicating the associated ECTS credits and the number of hours. This portfolio will be submitted to the DATA Programme’s assessment panel, which will determine the partial or full recognition of these prior achievements.

2. Training Offer within the DATA Programme

Students have the option to complete the minor by selecting courses from the DATA Programme's offerings (pre-sessional weeks, PSL Weeks, hackathons, etc.). Details are provided below.
Note: The two pre-sessional weeks offered by the DATA Programme serve as prerequisites for the certificate, unless the student can demonstrate equivalent prior learning.

3. DATA-Accredited Courses within PSL University’s Graduate Programmes

Students may also validate the minor by taking master’s courses accredited by the DATA Programme within their own graduate curriculum (according to their respective graduate programme).
Graduate programmes offering DATA-accredited courses from the 2023 academic year include:
•   Courses from the Graduate Programme in Economics
•   Courses from the Graduate Programme in Finance
•   Courses from the Graduate Programme in Cognitive Sciences
•   Courses from the Graduate Programme in Physics
•   Courses from the Engineering Cycle at ESPCI Paris – PSL

How to validate the DATA minor ?

Students who have accumulated 30 ECTS credits according to the aforementioned criteria must compile a dossier containing:

A brief overview of their background (identity, education, and institution of enrolment) and a copy of their student ID card (or proof of enrolment)
A list of the courses completed or internships undertaken that may be eligible for validation under the Data Minor
Proof of validation (official transcript from their institution) indicating the associated ECTS credits

This dossier should be submitted to mineuredata@psl.eu with the subject line "Request for Validation of the Data Minor". Each year, a panel convenes in December, and the deadline for dossier submission is 15 November (23:59, Paris time).
Note: If the submitted dossier includes courses with very similar content, only one of these courses will be counted towards the 30 ECTS required. In case of doubt, students may consult their original programme coordinator or contact mineuredata@psl.eu.

Recognition of Prior Learning: Students who have already completed courses or acquired skills in the field of Data Science may compile a dossier with the following supporting documents: the syllabus of the relevant course and proof of validation indicating the number of ECTS credits awarded and the number of hours. This dossier will be reviewed by the DATA Programme’s assessment panel, which will determine the partial or full recognition of these prior achievements.

Training opportunities in AI and Data Science within the DATA programme

Pre-term weeks (6 ECTS)

Two pre-term weeks are offered. They serve as mandatory prerequisites for the certificate (unless the student can demonstrate equivalent prior learning from their previous studies).

Week 1 – Mathematical and Computing Fundamentals (3 ECTS): The mathematical and computing foundations for data science. This week is delivered asynchronously.
Week 2 – Machine Learning and Databases (3 ECTS): This week takes place in person.

2024 Programme:

Week 1 – Mathematical and Computing Fundamentals (3 ECTS): Accessible on the Moodle platform from mid-August 2024. Further information will be provided.

Registration deadline: Friday, 19 July 2024, 12:00 PM.

Week 2 – Machine Learning and Databases (3 ECTS): This week will be held in person from Wednesday, 28 August to Tuesday, 3 September 2024, from 9:00 AM to 5:30 PM at L’Estrapade, 16 bis rue de l'Estrapade, 75005 Paris.

Registration deadline: Friday, 19 July 2024, 12:00 PM.

2024 Assessment:

Separate assessments will be conducted for the two weeks:

Week 1: 05/09/2024, from 5:00 PM to 6:00 PM online.
Week 2: 06/09/2024, from 5:00 PM to 6:00 PM online.

Intensives DATA Weeks (1 PSL Week = 2 ECTS)

Semester 1: 25 to 29 November 2024:

Ethics and Artificial Intelligence
NLP for Social Sciences
Toward AI Sustainability: Low-Level Optimisation for High Impact
Statistical Physics and Machine Learning
Neuro and Bio-Robotics: Senses and Perception
Explainable and Interpretable Artificial Intelligence
Image Analysis: From Theory to Practice

Semester 2: 3 to 7 March 2025:

AI for Economics and Finance
Data Mining and Modelling for Behavioural Sciences and Beyond
Digital Humanities Meet Artificial Intelligence
Machine Learning for Physics and Engineering
Large-Scale Machine Learning

Hackathons (6 ECTS)

The hackathons (6 ECTS) enable a group of students to develop a scientific project at the intersection of AI and their discipline over a period of 8 weeks, with technical supervision.