The introduction module helps students to refresh or acquire the minumum skills required for start DTAM course. Here you can find fundamentals skills about PC Systems and Raspberry Pi, Networking, Python programming, Databases, Electronics and Sustainability.

This course is for technicians and professionals who would like to access and improve learning process on a different and pioneering way. At the end of the module, on a personal level you will have the ability to achieve individual learning, adapt on different situations, find innovative ideas and surpass difficulties. It is well known that a strong and complete personality is the first step on professional success. Furthermore, on social level you will be able to communicate with other people and cooperate properly. Last but not least, you will enrich your knowledge with the ability to handle effectively big information volume.

Upon completion of the module the student will be able to:

  • Understand which is the level structure of an Industrial Control System (ICS).
  • Know which are the main components of each of the ICS levels.
  • Describe the functionality of the main components of an ICS.
  • Understand the importance of conectivity in an ICS.
  • Identify the different physical topologies of an ICS equipment.
  • Describe the main communication protocols in industrial networks.
  • Identify communication equipment used in an industrial network.
  • Identify which are the some of the most important industrial network protocols.
  • To understand OT/IT integration cybersecurity implications.
  • To understand which are the most usual cybersecurity hazarda and risks.
  • To identify an ongoing attack on industrial systems like the prementioned ones.
  • To be able to planify countermeasures to prevent a cyber-attack on industrial systems.
  • Comprehend the concept of availability, all the phases envolved (fault avoidance, detection and tolerance) and measures required to decrease unavailability.
  • Comprehend the importance of a security policies and contingency plans.
  • Apply measures described in contingency plans that are related with their role in the organisation in case of a disaster.
  • Comprehend the importance of Data Confidentiality and Integrity and the be able to identify and apply measures that should be taken to ensure that.

This course is an introduction to Machine Learning and includes key concepts. Learners will be able to implement machine learning applications end-to-end in Python following defined steps and choose appropriate Python library depends on the problem that needs to be solved.

This course is for technicians and professionals who would like to understand the core tools used to wrangle and analyze big data, as well as the core tools used for distributed processing of large data sets across clusters of computers. Although the tools that are presented are generally applicable for data processing, analysis and visualization, the module is mainly oriented for advanced manufacturing use cases. At the end of the module, you will learn how to use Python for data analysis and data visualization. Moreover, you will learn how to use the Hadoop framework for distributed processing of large data sets.