Espandi tutto

Digital self-evaluation tool

IOT LAB

Reserve a timeslot in one of our IOT labs

Introduction

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.


Transversal Skills

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.

Cybersecurity

This course is for technicians and professionals who would like to define and implement security strategies in industrial organizations and infrastructures. At the end of the module you will learn how to perform cybersecurity diagnostics, identifying vulnerabilities and implementing the necessary measures to mitigate them, applying the necessary measures to mitigate them by applying the current regulations and industry standards, following the sector standards, following the protocols of quality, occupational risk prevention and environmental respect.

Advanced sensors

This course will introduce different sensors, devices to connect the sensors to data storage services, networking solutions and data processing solutions. The course involves working with Raspberry PI's, Arduino's, NodeRed, Grafana, programming sensors using Python, and network communication over TCP/IP, Zigbee, LoRa, Bluetooth, 4G/5G cellular networks, 433MHz, and Z-wave. Data is sent to a MySQL database or a message bus (MQTT).

Machine Learning

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.



Big Data

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.