Data Science in Smart City (Summer 2022)

Note: The primary platform for communication in this course will be StudIP. All materials will be uploaded there.

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Details

Workload/ECTS Credits:	180h, 6 ECTS
Module:	M.Inf.1800 Fortgeschrittenen Praktikum Computernetzwerke
Lecturer:	Prof. Xiaoming Fu; Zhengze Li
Teaching assistant:	Zhengze Li, Weijun Wang
Time:	Mondays 8:00 - 10:00
Place:	(online)
UniVZ	[1]

Course Organization

In this course, you will complete several practical tasks in the realm of data analysis. These tasks can include both exploratory (descriptive) data analysis as well as the application of machine learning algorithms to specific datasets.

While the focus of the course is strongly practical, to support students, the course will provide lectures on different aspects of practical machine learning in the early stages of the course, including:

• Introduction to the practical data science pipeline
• Exploratory data analysis
• The Python Data Science stack
• Video Analytics

Students need to finish three tasks by specific deadlines throughout the course. Note that this course thus requires a continuous effort throughout the whole semester. A final report needs to be submitted at the end of the semester (September 30).

Schedule

When?	What?
04.04.2022 8:00-10:00	Lecture 1
11.04.2022 8:00-10:00	Lecture 2
18.04.2022 8:00-10:00	Lecture 3 & Release of Task 1
25.04.2022	No Lecture
02.05.2022 8:00-9:00	Intermediate meeting of Task 1
09.05.2022 8:00-10:00	Lecture 4 & Task 1 report submission (Before 10PM)
16.05.2022	Lecture 5 & Release of Task 2
06.06.2022	Task 2 report submission (Before 10PM)
07.06.2022	Release of Task 3
20.06.2022 8:00-9:00	Intermediate meeting of Task 3
TBD	Final Presentation
TBD	Final Report deadline (Including report and code)