Data science for the Internet of Things
Max amount of FITech students: 15
Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.
The course covers the fundamentals of developing data science processing pipelines for data produced by Internet of Things devices.
The Internet of Things (IoT) is an extension of Internet connectivity into everyday objects and physical devices. Modern IoT devices integrate many sensors which provide measurements characterising the device, its environment, or its user. These data are emerging as one of the fastest growing areas for data science.
The data science for the Internet of Things course covers the fundamentals of developing data science processing pipelines for data produced by Internet of Things devices. The course covers all common phases within data science pipelines: data collection, ground truth collection, feature engineering, and data modelling and evaluation.
- Introduction to the Internet of Things, pervasive computing, data science
- Sensing and signal processing
- Pipelines and programming of data science for the Internet of Things
- Privacy and security for data science for the Internet of Things
- Challenges and opportunities of data science for the Internet of Things Systems.
After this course you will be able to
- identify and discuss emerging challenges and opportunities of data science for the Internet of Things
- conceptualise and devise new applications that utilize the power of IoT and data science
- design, implement, analyse, and evaluate data science pipelines for the Internet of Things.
- The course does not follow any coursebook or set of papers. Each lecture is prepared individually. The teaching materials give references for further readings at the end of each lecture slide set.
- The course material (lectures, exercises, and selected solutions) will be available in Moodle.
- Lectures Mon 14-16 and Tue 10-12
- Exercises Wed 10-12
The course will be offered in contact teaching. Grading is based on the home exam and weekly exercises.
More information in the University of Helsinki study guide.
You can get a digital badge after completing this course.
IoT esineiden internet asioiden internet tekoäly koneoppiminen ML hajautettu oppiminen syväoppiminen tietojenkäsittelytiede
Further information about the course and studying
Contact person for applications
AI and machine learning,