Deploying Deep Learning Using a Microcontroller 26-27 S2

The DEPLOYING DEEP LEARNING USING A MICROCONTROLLER course aims to provide students with knowledge on:

• The architecture and applications of digital signal processors (DSPs) and embedded systems.
• The principles of real-time digital signal processing and edge AI deployment.
• The use of camera-based detection systems and motion sensors in embedded applications.
• Deep learning implementation on resource-constrained devices and microcontroller platforms.
• Programming techniques for digital signal processors, microcontrollers, and embedded AI platforms.
• Runtime environments and development frameworks used for deploying machine learning models on embedded systems, including NVIDIA Jetson platforms.

The programme of the course is divided into units:

1. Hello, AI World Setup.
2. Image Classification Inference.
3. Training Image Classification Models.
4. Object Detection Inference.
5. Training Object Detection Models
6. Semantic Segmentation and other Advanced Architectures.

For a detailed description of the course, please refer to the course study guide above (it will open in a new tab).

Timetable:

Lectures will take place every Saturday, starting on 3 April, and will last approximately four hours each.

• 03.04.27 – 4h
• 10.04.27 – 4h
• 17.04.27 – 4h
• 24.04.27 – 4h

• EUNICE bachelor’s student: enrolled as a student in one of the universities of EUNICE European University consortium (check the partner universities here).
• The student should have basic knowledge on: programming, telecommunications, mathematics.
• The student should have the ability to obtain information from the indicated sources and be ready to cooperate as part of the team.
• The student should have knowledge in the field of digital electronics and the ability to design numerical algorithms and programming microprocessor systems at the level of first-cycle studies.
• English B2.

Study Level: Bachelor, Master

• Submit your application via the button ‘Apply Now’.
• Please keep in mind that the number of participants could be limited for each course. Application does not guarantee enrolment in the course.
• The course participants will be selected based on criteria specified in the study guide.
• Your home university will inform you whether you have been accepted and provide further information about the next steps.

Specific instructions in some universities:

• BTU students: a Learning Agreement must be completed in advance in coordination with your departmental advisor. Please contact your examination office and study programme coordinator in good time once you are accepted for the courses you would like to attend. For any other questions you can contact: eunice@b-tu.de
• UPHF students: make sure to ask the approval of your director of studies (responsable pédagogique) before applying. For any question, you can contact the EUNICE office: eunice@uphf.fr
• UoP students: questions about enrolment and recognition can be answered by your Director of Studies or ECTS Coordinator, or you can contact eunice@go.uop.gr

Any questions about enrolment or credit recognition? Contact your EUNICE courses coordinator.