MACHINE LEARNING IN CHEMICAL RESEARCH
MACHINE LEARNING IN CHEMICAL RESEARCH
| A.Y. | Credits |
|---|---|
| 2024/2025 | 8 |
| Lecturer | Office hours for students | |
|---|---|---|
| Giovanni Bottegoni |
| Teaching in foreign languages |
|---|
|
Course entirely taught in a foreign language
English
This course is entirely taught in a foreign language and the final exam can be taken in the foreign language. |
Assigned to the Degree Course
| Date | Time | Classroom / Location |
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| Date | Time | Classroom / Location |
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Learning Objectives
The primary goal of the module is to present and analyze case studies on the application of machine learning techniques to chemical sciences. Particular emphasis will be placed on exploring the potential and opportunities provided by modern deep learning techniques. These case studies will serve as practical examples to illustrate how advanced computational methods can address complex challenges in chemistry, ranging from data analysis to predictive modeling and beyond.
Program
- Introduction to the Course
- Machine Learning in the Context of Computer-Assisted Molecular Design
- Representation of Molecules
- Supervised Learning in Chemical Sciences
- Unsupervised Learning in Chemical Sciences
- Deep Learning in Chemical Sciences
- LLMs in Chemical Sciences
Teaching Material
The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it
Teaching, Attendance, Course Books and Assessment
- Assessment
Each student will have to write a brief essay (1500 - 2000 words max, including title and a few references) on the application of machine learning to chemical sciences.
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
| « back | Last update: 24/01/2025 |
