Participate in the open online course “Machine Learning and Big Data for Bioinformatics” 

The University of Granada invites the Arqus community to participate in the 5th edition of the MOOC “Machine Learning and Big Data for Bioinformatics”, which will begin on 10 March 2025. Registration is already open!

Available fully in English and Spanish, this massive open online course lasts 100 hours (8 weeks + 1 additional week to finish any pending content) and is delivered in asynchronous mode. The course starts on 10 March and finishes on 12 May. Registration will remain open until then. It is possible to obtain an academic recognition certificate after completing the course.

The University of Granada aims to offer practical and applied learning that is accessible to all interested in Machine Learning and Big Data for Bioinformatics. For this purpose, it has a group of university professors, researchers, professionals, and specialists in each area, who will help introduce Bioinformatics and Machine Learning in their broadest aspects, combining academic rigor with a simple and direct methodology for understanding and enjoyment.

Every Monday, all available material for the module to be covered that week will be added to the abiertaUGR platform. Students learn through videos, materials, and didactic resources provided by the teaching team, without face-to-face classes nor fixed schedules. The temporal planning is designed to work on one module each week, but each student can make the temporal planning that best suits their needs. 

The course is delivered through the University of Granada’s online open training platform (abiertaUGR) and consists of 8 modules:

1. Module 1: What is bioinformatics? Module Coordinators: Carlos Cano, Coral del Val, and Pedro Carmona.
2. Module 2: Bioinformatics analysis on an omics problem. Module Coordinators: Carlos Cano, Coral del Val, and Pedro Carmona.
3. Module 3: Data science and machine learning. Module Coordinator: Alberto Fernández Hilario.
4. Module 4: Supervised learning: Regression techniques. Module Coordinator: Rafael Alcalá Fernández.
5. Module 5: Supervised learning: Classification techniques. Module Coordinator: Alberto Fernández Hilario.
6. Module 6: Unsupervised learning: Clustering and association rules. Module Coordinator: Jesús Alcalá Fernández.
7. Module 7: Big Data. Module Coordinator: Francisco Javier García Castellano.
8. Module 8: Graphic tool: KNIME. Module Coordinators: María Martínez and José Manuel Soto.

Registration and more information at the abiertaUGR website.