Advanced Practical Course Data Science (Winter 2020/2021): Difference between revisions
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=180h, ..." |
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|credits=180h, 6 ECTS | |credits=180h, 6 ECTS | ||
|module=M.Inf.1800 Fortgeschrittenen Praktikum Computernetzwerke | |module=M.Inf.1800 Fortgeschrittenen Praktikum Computernetzwerke | ||
|lecturer=[http://134.76.18.81/?q=people/prof-dr-xiaoming-fu Prof. Xiaoming Fu]; [http:// | |lecturer=[http://134.76.18.81/?q=people/prof-dr-xiaoming-fu Prof. Xiaoming Fu]; [http://www.net.informatik.uni-goettingen.de/?q=people/jiaquan-zhang MSc. Jiaquan Zhang] | ||
|ta=[http://www.net.informatik.uni-goettingen.de/people/ | |ta=[http://www.net.informatik.uni-goettingen.de/?q=people/jiaquan-zhang MSc. Jiaquan Zhang] | ||
|time= | |time=Friday 16:00-18:00 | ||
|place= | |place=2.101(online) | ||
|univz=[https://univz.uni-goettingen.de/qisserver | |univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=256838&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&idcol=k_semester.semid&idval=20202&getglobal=semester&htmlBodyOnly=true] | ||
}} | }} | ||
==Announcement== | ==Announcement== | ||
Due to the recent | '''20.10.2020 Our first lecture will be on 06.11.2020 through the Meeings tool on StudIP''' | ||
'''30.09.2020 Our course in this semeter will be online''' | |||
'''Due to the recent situations in the context of Covid-19, how to arrange the lectures in this winter semester is still not determined (online or face-to face lecturing, when and where are the lectures, how is presentation arranged). Any new information will be updated here in time, please check this webpage periodically to get the newest information. | |||
''' | |||
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|{{Hl2}} |'''What?''' | |{{Hl2}} |'''What?''' | ||
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| align="right" | | | align="right" | 06.11.2020 | ||
| Lecture 1: Introduction & The Data Science Pipeline | | Lecture 1: Introduction & The Data Science Pipeline | ||
|- | |- | ||
| align="right" | | | align="right" | 13.11.2020 | ||
| Lecture 2: The Python Data Science Stack - Task 1: Release | | Lecture 2: The Python Data Science Stack - Task 1: Release | ||
|- | |- | ||
| align="right" | | | align="right" | 20.11.2020 | ||
| No lecture | | No lecture | ||
|- | |- | ||
| align="right" | | | align="right" | 27.11.2020 | ||
| Task 1: Intermediate meeting | | Task 1: Intermediate meeting | ||
|- | |- | ||
| align="right" | | | align="right" | 04.12.2020 | ||
| | | // Task 1 report submission //Task 2: release | ||
|- | |- | ||
| align="right" | | | align="right" | 11.12.2020 | ||
| | | No lecture | ||
|- | |- | ||
| align="right" | | | align="right" | 18.12.2020 | ||
| | | Lecture 3: Advanced Algorithms for Data Science | ||
|- | |- | ||
| align="right" | | | align="right" | 25.12.2020 | ||
| | | No lecture // Task 2 report submission | ||
|- | |- | ||
| align="right" | | | align="right" | 01.01.2021 | ||
| No lecture | | No lecture (holidays) | ||
|- | |- | ||
| align="right" | | | align="right" | 08.01.2021 | ||
| No lecture | | No lecture (holidays) | ||
|- | |- | ||
| align="right" | | | align="right" | 15.01.2021 | ||
| Task 3: | | Lecture 4: Evaluation and Tuning of Models // Task 3: release | ||
|- | |- | ||
| align="right" | | | align="right" | 22.01.2021 | ||
| No lecture | | No lecture | ||
|- | |- | ||
| align="right" | | | align="right" | 29.01.2021 | ||
| Task 3: Intermediate meeting | | Task 3: Intermediate meeting | ||
|- | |- | ||
| align="right" | | | align="right" | 05.02.2021 | ||
| | | Final Presentation (TBD) | ||
|- | |- | ||
| align="right" | | | align="right" | 12.02.2021 | ||
| | | Final Presentation (TBD) | ||
|- | |- | ||
| align="right" | | | align="right" | 31.03.2021 | ||
| Final Report deadline (Including report and code) | | Final Report deadline (Including report and code) | ||
|- | |- | ||
|} | |} | ||