Master's Degree in Industrial Computing and Robotics

2020/2021 · 60 credits

Professional and academic career

Planning for teaching

This study has teaching guide
You can read it to learn more about the study. In the table below you can see the individual teaching guides for each subject.

Study structure

The masters are organized by modules. Click on a module for more information.

  Guide Type QTR. credits
Industrial Drives Compulsory 1st 4.5 ECTS
Advanced Automation Compulsory 1st 4.5 ECTS
Embedded Systems Compulsory 1st 4.5 ECTS
High-level Languages for Industrial Applications Compulsory 1st 4.5 ECTS
Smart Robotics and Autonomous Systems Compulsory 1st 4.5 ECTS
Virtual Instrument Programming Compulsory 1st 4.5 ECTS
Industrial Automation Optional 1st 3 ECTS
Control Technology Optional 1st 3 ECTS
Computer Communications Networks Optional 1st 3 ECTS
Information Systems in Industrial Environments Optional 1st 3 ECTS
  Guide Type QTR. credits
Introduction to Python for Engineers Optional 2nd 3 ECTS
Python for Engineers. Advanced Optional 2nd 3 ECTS
Robotics Application Development: Introduction to ROS Optional 2nd 3 ECTS
Robotics Application Development: Advanced ROS Optional 2nd 3 ECTS
Autonomous Robotics Applications Optional 2nd 3 ECTS
Machine Learning I Optional 2nd 3 ECTS
Machine Learning II Optional 2nd 3 ECTS
Machine Vision I Optional 2nd 3 ECTS
Machine Vision II Optional 2nd 3 ECTS
Mobile Robotics Optional 2nd 3 ECTS
Emerging Manufacturing Technologies Optional 2nd 3 ECTS
Emerging Manufacturing Technologies Workshop Optional 2nd 3 ECTS
Mechanics of Robotic Systems Optional 2nd 3 ECTS
Simulation and Analysis of Robotic Systems Optional 2nd 3 ECTS
  Guide Type QTR. credits
Industrial Communications and Real-time Systems Optional 2nd 3 ECTS
Cyber-physical Systems Optional 2nd 3 ECTS
Industrial IoT Optional 2nd 3 ECTS
Big-data & Analytics Optional 2nd 3 ECTS
Augmented Reality, Artificial Vision Optional 2nd 3 ECTS
Additive Manufacturing Optional 2nd 3 ECTS
Smartcities - Smartregions Optional 2nd 3 ECTS
Simulation for Industry 4.0 Optional 2nd 3 ECTS
Computational Intelligence Optional 2nd 3 ECTS
Cloud Computing Optional 2nd 3 ECTS
Signal Processing with Machine Learning Optional 2nd 3 ECTS
Metaheuristics Optional 2nd 3 ECTS
  Guide Type QTR. credits
Work Placement Compulsory 2nd 3 ECTS
  Guide Type QTR. credits
Master's Dissertation Compulsory 2nd 9 ECTS

Teachers

The study is taught by the following teachers:

The masters are organized by modules. Click on a module for more information.

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Student mobility

UDC holds student mobility agreements with universities and other third-level institutions across four continents. Students are offered several opportunities each year to apply to study abroad in one of these centres (for a single term or for a whole year), with the guarantee that all credits obtained will be duly recognised in their academic record upon their return.

For each round of applications, the University publishes the list of exchange options available to students and, where relevant, the specific conditions associated with each. Students may also apply to the University for funding for international work experience placements and internships.

Work experience placements are accredited in the student's academic record and the European diploma supplement. Students are free to decide in which host company or academic institution within the EHEA they wish to carry out their placement. To assist them in their search, the University has created an online noticeboard with jobs postings and other news.

Work-study placements in A Coruña are arranged by the International Relations Office (ORI) of the UDC in collaboration with the international relations coordinators in the student’s home university. The general entry criteria, rights and obligations of students, and admission and acceptance procedures for the programme, are regulated by the UDC Mobility Policy.