Summer course: Fundamentals of Machine Learning

The Machine Learning Fundamentalscourse is designed for students who wish to enter the fascinating world of machine learning applied to industrial engineering and advanced technological sectors. In a Smart Industry context, Machine Learning has become an essential tool to optimise processes, predict trends and make informed decisions. This course offers a theoretical-practical approach that allows students to master the most advanced techniques and algorithms in classification, regression, unsupervised learning and time series analysis, using tools such as Python and cutting-edge libraries such as Scikit-Learn and PyTorch.

Dates: From July 2nd to July 18th 2025.

Why study this course?

In a world where data is key to innovation, having a solid foundation in Machine Learningis an indispensable skill for the engineers of the future. This course not only provides the fundamental knowledge in machine learning techniques, but also allows them to apply these tools to real problems, optimising industrial processes and improving decision making. In addition, students will learn to use advanced algorithms in Python, one of the most sought-after skills in the technology industry. Upon completion, they will be able to design and train machine learning systems applicable to different sectors, positioning themselves at the forefront of digital transformation.

A diploma will be awarded by the University!

Course description

Duration: 3 weeks (approximately 60 hours).
Credits: 6 ECTS.
Language: Spanish.
Place: C/Alberto Aguilera, 23, Madrid.
Requirements:students who are studying for a degree, preferably between the second and third year. If the course is taught in English, a minimum B2 certificate in this language will be required.
Enrolment: to carry out this procedure, please contact(comillas.internacional@comillas.edu).
Enrolment deadline:until 15 May. Check availability after the enrolment date atcomillas.internacional@comillas.edu .
Price: 1,200 euros.
- Early Bird!20% discount for registrations made before 15 April.