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| en:iot-reloaded:curriculum:data [2024/05/03 18:13] – [Table] karlisberkolds | en:iot-reloaded:curriculum:data [2024/12/10 17:20] (current) – pczekalski |
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| ====== Module: Data Analytics ====== | ====== Module: IoT Data Analysis (M3) ====== |
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| | **Study level** | Master || | | **Study level** | Master || |
| | **Type of assessment** | Prerequisite of a positive grade is a positive evaluation of course topics and presentation of practical work results with required documentation || | | **Type of assessment** | Prerequisite of a positive grade is a positive evaluation of course topics and presentation of practical work results with required documentation || |
| | **Blended learning** | Along with MOOC course in hybrid mode. || | | **Blended learning** | Along with MOOC course in hybrid mode. || |
| | **References to\\ literature** | 1. M Vergin Raja Sarobin, J Ranjith, D Ashwath, K Vinithi, Smiti, V Khushi, Comparative Analysis of Various Feature Extraction Methods on IoT 2023, Procedia Computer Science (2024) Elsevier. || | | **References to\\ literature** | 1. M Vergin Raja Sarobin, J Ranjith, D Ashwath, K Vinithi, Smiti, V Khushi, Comparative Analysis of Various Feature Extraction Methods on IoT 2023, Procedia Computer Science (2024) Elsevier. \\ 2. Dina Fawzy, Sherin M. Moussa, Nagwa L. Badr, An IoT-based resource utilization framework using data fusion for smart environments, Internet of Things, (2023) Elsevier. || |
| | **Lab equipment** | || | | **Lab equipment** | || |
| | **Virtual lab** | || | | **Virtual lab** | || |
| | **MOOC course** | http://edu.iot-open.eu/course/view.php?id=8 || | | **MOOC course** | http://edu.iot-open.eu/course/view.php?id=8 || |
