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Data Science in Smart City (Winter 2022/2023): Difference between revisions

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Data Science in Smart City (Winter 2022/2023) (view source)

Revision as of 12:42, 30 January 2023

212 bytes added ,  30 January 2023
→‎Schedule
(Created page with "{{Announcement|Note: The primary platform for communication in this course will be StudIP. All materials will be uploaded there.}} == Details == {{CourseDetails |credits=180...")
 
 
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|lecturer=[http://134.76.18.81/?q=people/prof-dr-xiaoming-fu Prof. Xiaoming Fu]; [http://www.net.informatik.uni-goettingen.de/?q=people/zhengze-li Zhengze Li]
|lecturer=[http://134.76.18.81/?q=people/prof-dr-xiaoming-fu Prof. Xiaoming Fu]; [http://www.net.informatik.uni-goettingen.de/?q=people/zhengze-li Zhengze Li]
|ta=Zhengze Li, Bowen Li
|ta=Zhengze Li, Bowen Li
|time=Monday 8:00 - 10:00am
|time=Monday 10:00 - 12:00am
|place= IFI 0.101
|place= IFI 0.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds;jsessionid=A8B3DFB635EA200C7E9420D0B180F622.s45?state=verpublish&status=init&vmfile=no&publishid=302542&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
|univz=[https://ecampus.zvw.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&_flowExecutionKey=e5s12]
}}
}}


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* Read state-of-art papers.
* Read state-of-art papers.
* Use programming to build systems including computer vision algorithms, embedded design programs, and SOCKET network programs.
* Use programming to build systems including computer vision algorithms, embedded design programs.
* Learn how to analyze city public transport sensor data.
* Learn how to analyze city public transport sensor data.


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|-
|-
| align="left" | 31.10.2022
| align="left" | 31.10.2022
| No Lecture (Reformationstag)
|-
| align="left" | 07.11.2022
| Lecture 2
| Lecture 2
|-
|-
| align="left" |  
| align="left" | 14.11.2022
| Lecture 3 & Release of Task 1
| Lecture 3 & Release of Task 1
|-
|-
| align="left" |  
| align="left" | 21.11.2022
| Intermediate meeting of Task 1
| Intermediate meeting of Task 1
|-
|-
| align="left" |  
| align="left" | 28.11.2022
| Task 1 report submission (Before 10PM)
| Task 1 report submission (Before 10PM)
|-  
|-  
| align="left" |  
| align="left" | 05.12.2022
| Lecture 4 & Release of Task 2
| Lecture 4 & Release of Task 2
|-
|-
| align="left" |  
| align="left" | 12.12.2022
| Intermediate meeting of Task 2
|-
| align="left" | 19.12.2022
| Task 2 report submission (Before 10PM)
| Task 2 report submission (Before 10PM)
|-
|-
| align="left" |  
| align="left" | 26.12.2022
| No Lecture. (2. Weihnachtsfeiertag)
|-
| align="left" | 02.01.2023
| No Lecture. (Vorlesungsfreie Zeit)
|-
| align="left" | 09.01.2023
| Release of Task 3
| Release of Task 3
|-
|-
| align="left" |  
| align="left" | 30.01.2023
| Intermediate meeting 1 of Task 3
| Intermediate meeting Task 3
|-
|-
| align="left" |  
| align="left" | 17.02.2023
| Intermediate meeting 2 of Task 3
|-
| align="left" |
| Report Submitting  
| Report Submitting  
|-
|-
| align="left" |
| align="left" | 21.02.2023
| Final Presentation
| Final Presentation
|-
| align="left" | 27.02.2023
| Final report submission
|-
|-
|}
|}
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