Machine Learning for IoT Lighting
The table below shows a suggested list of courses for an M.Sc. graduation track at Machine Learning for IoT Lighting. This track has an emphasis on the use of machine learning for sensing biological process estimation.
Quartile | Course Code | Course Name | Course Type | ECTS |
Y1-Q1-A | 5CTA0 | Statistical signal processing | Core | 5 |
Y1-Q1-B | 2DME30 | Complex analysis | Core | 5 |
Y1-Q1-C | 2DME20 | Non-linear optimization | Core | 5 |
Y1-Q1-E2 | 5CKF0 | Research set-up | Prof. Dev. | 2.5 |
Y1-Q3-B1 | 5SSC0 | Adaptive array signal processing | Specialization | 5 |
Y1-Q3-B2 | 5SSD0 | Bayesian machine learning and information processing | Specialization | 5 |
Y1-Q4 | 5CKB0 | Tutoring and coaching | Prof. Dev. | 2.5 |
Y1-Q4-A2 | 5LSL0 | Machine learning for signal processing | Elective | 5 |
Y1-Q4-D1 | 5AUA0 | Advanced sensing using Deep Learning | Elective | 5 |
Y2-Q1 | 5M815 | Internship SPS | Graduation | 15 |
Y2-Q2,Q3,Q4 | 5T845 | Graduation project SPS | Graduation | 45 |
Contact
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Imke Brouwer DZeynep Schuylenborch PhDde Voslaan5171GH Vinkelmilou.zowranvonranzow@ live.nl
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Rens BartelsNout Veenstra Mscde Koningpad4382NC It Heidenskipnynke.zeemans@ hotmail.nl