Courses / Department of Electrical and Computer Engineering

Training course - Robotics and Applied Machine Learning

General Objectives of the Course

The main goal is for students (bachelors, master or early-PhD) to understand the fundamentals (both theory and practical) of Mobile Robotics, Automated Systems, and Machine Learning and their applications to real-world problems. The programme is divided in two modules: (i) Hardware and software for mobile robotics; and (ii) Applied machine learning. The first module will cover the fundamental and principles of mobile robotics and automation, while the latter is more devoted to the theoretical and practical elements of artificial perception, learning and computational intelligence.

Admission Requirements

Bachelor, Masters’ or PhD student.

Candidates should check the admission requirements available on this site, in addition to the information provided here.

Mode of Study

Face-to-face

Teaching / Evaluation language(s)

Portuguese and English

Examination Regulations, Assessment and Grading

Approved, Approved With Honors, Approved With Great Honors, Approved With Highest Honors).

Learning Objectives and Intended Skills

On completion of this Summer School students should be able to: understand the key aspects of mobile robotics and automated systems; understand principles of common robotics and AI/ML algorithms; understand the key components related to real-world applications. Skills and Attributes: (i) Intellectual /cognitive skills: solve robotics and machine learning problems according to a 'hardware-in-the-loop' paradigm; develop models, algorithms and testing on actual robotic platforms; maintain a sound theoretical/systematic approach on real-world implementations. (ii) Practical: use software and hardware to develop tailored robotics & ML systems; evaluate the performance of algorithms for autonomous robotics problems. (iii) Transferable: communicate effectively with colleagues and others using both written and oral methods; familiarize with coding, algorithm development, and hardware (actual robots) operation; manage resources and time; become analytical in the formulation and solution of engineering problems.

Qualification Requirements and Regulations

Regulation n. 339/2012, published in Diário da República n. 152, 2.nd series, of August 7th (“Regulamento de Criação e Funcionamento de Cursos não Conferentes de Grau na Universidade de Coimbra”).

Study Programme

Robótica e Aprendizagem Computacional
Academic year
2024-2025

Course Type
Non Degree Course

Qualification Awarded: Diploma/Certificate

Duration: 81 HORAS

ECTS Credits: 3.0

Applications

Call for Applications

Documents