Course catalogue
Create your own master’s programme by choosing between the different specializations of our partner universities.
Academic Programme
Implemented from September 2025
Data Science Basics (3 ECTS)
All courses during this semester
- Experimental methods on innovative research infrastructures - 5 ECTS
- Digital Micro-certification "The challenges of sustainable chemistry" - 10h
- Transferable skills : French language & interculturality (3 ECTS)
- Quantum mechanics towars quantum computing (5 ECTS)
- Winter school in Data Science (2 ECTS)
- Organic / Inorganic chemistry towards sustainability (5 ECTS)
- Kinetics and Electrochemistry (5 ECTS)
- Introduction to biophysics and microscopies for life science (5 ECTS)
All courses during this semester
- Luminescence spectroscopy of Lanthanides (3 ECTS)
- Summer School in Entrepreneurship (5 ECTS)
- Transferable skills: Polish course (3 ECTS)
- The molecules of life: from structure to chemical function (5 ECTS)
- Thermodynamics and soft matter (3 ECTS)
- Introduction to solid state (5 ECTS)
- Tech-infused perspectives on photochemical reaction dynamics (6 ECTS)
- Transferable skills: Portuguese course (3 ECTS)
- Summer School in Entrepreneurship (5 ECTS)
- Solid State Physics (5 ECTS)
- Molecular Energetics (3 ECTS)
- Laboratory of Materials and Surface Analysis (5 ECTS)
- Interfacial Electrochemistry (3 ECTS)
- Interfaces, Colloids and Self-Assembly (6 ECTS)
All courses during this semester
- 1-year research project - master thesis (equivalent 45 ECTS)
- Progress assessment of the research project (equivalent 6 ECTS)
- Weekly seminars (equivalent 4 ECTS)
- Special Topics in Chemistry (equivalent 5 ECTS)
- French language courses (3 ECTS)
- Nanosciences (6 ECTS)
- Medical applications of nanomaterials and radiations (6 ECTS)
- Top management, corporate law, and project writing for technology transfer and decision making (4 ECTS)
- Tracking ultrafast radiation-induced reactivity (3 ECTS)
- Applications for renewable energy and storage: solar fuels, batteries and hydrogen (6 ECTS) (6 ECTS)
- Scientific Writing and career objectives (2 ECTS)
- Surface Science and Nanostructuring at Surfaces (6 ECTS)
- Polymers for electronics and energy harvesting (5 ECTS)
- Electrochemical systems for fuel and electrolysis cells and batteries (6 ECTS)
- Project-based laboratory on device building (3 ECTS)
- Italian Courses (3 ECTS)
- Chemistry and Technology of Catalysis (5 ECTS)
Content
- The Cross-industry standard process for data mining (CRISP-DM) model.
- Data Collection and Business Understanding.
- Modelling
- Exploratory Data Analysis;
- Predictive Analytics.
- Evaluation methodologies.
Aims
The syllabus contents defined for this course unit are intended to provide the student with knowledge of the essential steps to a Data Science project. The goal is that the student will be able to define the problem, collect data, apply and evaluate some of the main modeling techniques and interpret the obtained results.
Recommended Books
- L. Torgo. Data Mining with R, learning with case studies, second edition, 2017. Chapman and Hall/CRC . ISBN: 9781482234893
- J. Han , M. Kamber and J. Pei. Data Mining - Concepts and Techniques (3rd edition), 2011. ISBN: 9780123814791.
Teaching Staff
Rita Ribeiro (responsible)
Hours
21 h (lectures + theoretical-practical classes)
Grading System
During classes topics will be exposed with the help of practical examples.
Evaluation will be carried out in a distribution form together with a final exam.
This course uses distributed evaluation formed by two (2) theoretical tests during the semester (or alternatively a final exam), and one (1) practical assignment at the end of the semester.
The final grade will be calculated as the weighted average of the practical and theoretical grades using the following formula:
NF = 0.60 * NTh + 0.40 * NPra
where, NTh is the average of the grades in the two tests or the grade in the final exam, and NPra is the grade of the practical assignment.