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
- Teacher: Jokin Goioaga
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).
- Teacher: Francien van Kan
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