NET Wiki - User contributions [en]

Advanced Practical Course Data Science (Winter 2019/2020)

2019-09-23T13:54:41Z

Sxu: /* Details */

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

== Details ==
{{CourseDetails
|credits=180h, 6 ECTS
|module=M.Inf.1800 Fortgeschrittenen Praktikum Computernetzwerke
|lecturer=[http://134.76.18.81/?q=people/prof-dr-xiaoming-fu Prof. Xiaoming Fu]; [http://134.76.18.81/?q=people/dr-yali-yuan Dr. Yali Yuan]
|ta=[http://www.net.informatik.uni-goettingen.de/people/jiaquan_zhang MSc. Jiaquan Zhang]; [http://www.net.informatik.uni-goettingen.de/?q=people/shuai-xu Shuai Xu]
|time=Friday, 16-18
|place=Ifi 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&veranstaltung.veranstid=253765 link]
}}

==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 machine learning pipeline
* Exploratory data analysis
* The Python Data Science stack
* How to deal with unbalanced data
* Advanced algorithms for Data Science (an overview of competition winning algorithms)
* Parameter tuning for predictive models

Students need to submit their solutions to tasks by specific deadlines throughout the course. Note that this course thus requires a continuous effort throughout the whole semester.
Solutions for each task have to be presented in class. A final report needs to be submitted at the end of the semester (September 30).

==Prerequisites==
*You are ''highly recommended'' to have completed a course on Data Science (e.g., "[https://www.swe.informatik.uni-goettingen.de/lectures/data-science-and-big-data-analytics-ws2015 Data Science and Big Data Analytics" taught by Dr. Steffen Herbold] or the Course "Machine Learning" by Stanford University) before entering this course. You need to be familiar with basic statistics (distributions, p/t/z-tests, etc.) and a range of machine learning algorithms (linear/logistic/lasso regression, k-means clustering, k-NN classification etc.).
*Knowledge of any of the following languages: Python (course language), R, JAVA, Matlab or any language that features proper machine learning libraries

==Schedule==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''When?'''
|{{Hl2}} |'''What?'''
|-
| align="right" | 25.10.2019
| Lecture 1: Introduction & The Data Science Pipeline
|-
| align="right" | 01.11.2019
| Lecture 2: The Python Data Science Stack - Task 1: Release
|-
| align="right" | 08.11.2019
| No lecture
|-
| align="right" | 15.11.2019
| Task 1: Intermediate meeting
|-
| align="right" | 22.11.2019
| Lecture 3: Advanced Algorithms for Data Science // Task 2: release
|-
| align="right" | 29.11.2019
| No lecture // Task 1 report submission
|-
| align="right" | 06.12.2019
| No lecture // Task 3: release
|-
| align="right" | 13.12.2019
| No lecture // Task 2 report submission
|-
| align="right" | 20.12.2019
| Lecture 4: Evaluation and Tuning of Models
|-
| align="right" | 27.12.2019
| Task 3: Intermediate meeting I
|-
| align="right" | 03.01.2020
| No lecture
|-
| align="right" | 10.01.2020
| Task 3: Intermediate meeting II
|-
| align="right" | 17.01.2020
| No lecture
|-
| align="right" | 24.01.2020
| No lecture
|-
| align="right" | 31.01.2020
| No lecture // Final slides submission (Only slides)
|-
| align="right" | 07.02.2020
| Task 3: Presentations (Final Presentation)
|-
| align="right" | 31.03.2020
| Final Report deadline (Including report and code)
|-
|}

Advanced Practical Course Data Science (Winter 2019/2020)

2019-09-23T13:54:08Z

Sxu: /* Details */

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

== Details ==
{{CourseDetails
|credits=180h, 6 ECTS
|module=M.Inf.1800 Fortgeschrittenen Praktikum Computernetzwerke
|lecturer=[http://134.76.18.81/?q=people/prof-dr-xiaoming-fu Prof. Xiaoming Fu]; [http://134.76.18.81/?q=people/dr-yali-yuan Dr. Yali Yuan]
|ta=[http://www.net.informatik.uni-goettingen.de/people/jiaquan_zhang MSc. Jiaquan Zhang http://www.net.informatik.uni-goettingen.de/?q=people/shuai-xu Shuai Xu]
|time=Friday, 16-18
|place=Ifi 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&veranstaltung.veranstid=253765 link]
}}

==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 machine learning pipeline
* Exploratory data analysis
* The Python Data Science stack
* How to deal with unbalanced data
* Advanced algorithms for Data Science (an overview of competition winning algorithms)
* Parameter tuning for predictive models

Students need to submit their solutions to tasks by specific deadlines throughout the course. Note that this course thus requires a continuous effort throughout the whole semester.
Solutions for each task have to be presented in class. A final report needs to be submitted at the end of the semester (September 30).

==Prerequisites==
*You are ''highly recommended'' to have completed a course on Data Science (e.g., "[https://www.swe.informatik.uni-goettingen.de/lectures/data-science-and-big-data-analytics-ws2015 Data Science and Big Data Analytics" taught by Dr. Steffen Herbold] or the Course "Machine Learning" by Stanford University) before entering this course. You need to be familiar with basic statistics (distributions, p/t/z-tests, etc.) and a range of machine learning algorithms (linear/logistic/lasso regression, k-means clustering, k-NN classification etc.).
*Knowledge of any of the following languages: Python (course language), R, JAVA, Matlab or any language that features proper machine learning libraries

==Schedule==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''When?'''
|{{Hl2}} |'''What?'''
|-
| align="right" | 25.10.2019
| Lecture 1: Introduction & The Data Science Pipeline
|-
| align="right" | 01.11.2019
| Lecture 2: The Python Data Science Stack - Task 1: Release
|-
| align="right" | 08.11.2019
| No lecture
|-
| align="right" | 15.11.2019
| Task 1: Intermediate meeting
|-
| align="right" | 22.11.2019
| Lecture 3: Advanced Algorithms for Data Science // Task 2: release
|-
| align="right" | 29.11.2019
| No lecture // Task 1 report submission
|-
| align="right" | 06.12.2019
| No lecture // Task 3: release
|-
| align="right" | 13.12.2019
| No lecture // Task 2 report submission
|-
| align="right" | 20.12.2019
| Lecture 4: Evaluation and Tuning of Models
|-
| align="right" | 27.12.2019
| Task 3: Intermediate meeting I
|-
| align="right" | 03.01.2020
| No lecture
|-
| align="right" | 10.01.2020
| Task 3: Intermediate meeting II
|-
| align="right" | 17.01.2020
| No lecture
|-
| align="right" | 24.01.2020
| No lecture
|-
| align="right" | 31.01.2020
| No lecture // Final slides submission (Only slides)
|-
| align="right" | 07.02.2020
| Task 3: Presentations (Final Presentation)
|-
| align="right" | 31.03.2020
| Final Report deadline (Including report and code)
|-
|}

Seminar on Internet Technologies (Winter 2019 2020)

2019-09-18T18:46:10Z

Sxu: /* Topics */

== Details ==

{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and [http://134.76.18.81/?q=people/yachao-shao Yachao Shao]
|time=Oct 24'''''', 13:00ct: Introduction Meeting
|place=IFI Building, Room 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=242639&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
{{Announcement|Note:
we will have Introduction Meeting on the second week of new Winter Semester}}

==Course description==

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

==Passing requirements==
*There will be 2 milestones before the presentations where the students should pass before they register for the course.
**Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
**Midterm milestone. (ex. programming tasks done etc... )

*Actively and frequently participate in the project communication with your topic advisor
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentation + 10 min. Q&A).
** This accounts for 40% of your grade.
* Write a report on the selected topic (12-15 pages) (LaTeX Template:[ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip]).
** This accounts for 40% of your grade.
* Please check the [[#Schedule]] and adhere to it.

==Schedule==
* '''Oct. 24 16:00ct''': Introduction meeting
* '''Decemeber 20th ''' : Deadline for registration
* '''Jan. 6 and Jan. 7 2020''' : Presentations
* '''Mar. 31, 2020, 23:59''': Deadline for submission of report (should be sent to the topic adviser!)

== Topics ==

{| align="center" class="wikitable sortable" {{Prettytable}}
|-
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Prerequisites'''
|{{Hl2}} |'''Topic Advisor'''
|{{Hl2}} |'''Initial Readings'''
|-
| '''Title (assigned to )'''
| intro
| requirement
| [Shichang Ding--sding@gwdg.de]
| []
|-
| Visible Light Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Power Line Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Autonomous Driving: Principles, Standardization and Prospects
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| V2X Communications: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| QUIC Protocols: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| Smart Cities: Principles, Case Studies and Prospects in EU and Worldwide
| In this project, you will be devoted to solving specific prediction problems based on the given data. These tasks nowadays are common concerns for building smart cities in practice. Just enjoy the interaction with real-world data!
| Since we will solve some practical problems based on data engineering, I think a strong programming ability is necessary. Python as well as Keras or Tensowflow or PyTorch are always preferred. Don't hesitate to contact me if you feel interested and have preliminary knowledge in related projects. Let's work together!
| [Shuai Xu, shuai.xu@cs.uni-goettingen.de]
| [http://www.public.asu.edu/~swang187/publications/VPOI.pdf],[https://arxiv.org/abs/1809.10770],[https://arxiv.org/abs/1811.02815],[https://arxiv.org/abs/1904.10322],[https://core.ac.uk/download/pdf/155789835.pdf]
|-
| Smart Grids: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Business Intelligence: Principles, Case Studies and Prospects
|
|
| [Yachao Shao, yshao@gwdg.de]
|-
| Logistics 4.0: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Digital Twin in Manufacturing: Principles, Standardization and Current Status in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Facial Recognition at Edge: Principles, Applications and Challenges
|
|
| [Xiaoming, xfu@gwdg.de]
|-
|}

==Workﬂow==

=== 1. Select a topic ===
A student picks a topic to work on. You can pick up a topic and start working '''at any time'''. However, make sure to notify the advisor of the topic before starting to work.

=== 2. Get your work advised ===
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

=== 3. Approach your topic ===

* By choosing a topic, you choose the direction of elaboration.
* You may work in different styles, for example:
** Survey: Basic introduction, an overview of the ﬁeld; general problems, methods, approaches.
** Specific problem: Detailed introduction, details about the problem and the solution.
* You should include your own thoughts on your topic.

=== 4. Prepare your presentation ===

* Present your topic to the audience (in English).
* 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the [http://www.net.informatik.uni-goettingen.de/ NET] group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation:
20 minutes are too short to present a topic fully.
It is alright to focus just on one certain important aspect.
Limit the introduction of basics.
Make sure to ﬁnish in time.

Suggestions for preparing the slides:
No more than 20 pages/slides.
Get your audiences to quickly understand the general idea.
Figures, tables and animations are better than sentences.
Summary of the topic: thinking in your own words.

=== 5. Write your report ===

* Present the problem with its background.
* Detail the approaches, techniques, methods to handle the problem.
* Evaluate and assess those approaches (e.g., pros and cons).
* Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

=== 6. Course schedule===
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the [[#Schedule]] to take appropriate actions.

[[Category:Courses]]

Seminar on Internet Technologies (Winter 2019 2020)

2019-09-18T18:45:03Z

Sxu: /* Topics */

== Details ==

{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and [http://134.76.18.81/?q=people/yachao-shao Yachao Shao]
|time=Oct 24'''''', 13:00ct: Introduction Meeting
|place=IFI Building, Room 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=242639&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
{{Announcement|Note:
we will have Introduction Meeting on the second week of new Winter Semester}}

==Course description==

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

==Passing requirements==
*There will be 2 milestones before the presentations where the students should pass before they register for the course.
**Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
**Midterm milestone. (ex. programming tasks done etc... )

*Actively and frequently participate in the project communication with your topic advisor
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentation + 10 min. Q&A).
** This accounts for 40% of your grade.
* Write a report on the selected topic (12-15 pages) (LaTeX Template:[ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip]).
** This accounts for 40% of your grade.
* Please check the [[#Schedule]] and adhere to it.

==Schedule==
* '''Oct. 24 16:00ct''': Introduction meeting
* '''Decemeber 20th ''' : Deadline for registration
* '''Jan. 6 and Jan. 7 2020''' : Presentations
* '''Mar. 31, 2020, 23:59''': Deadline for submission of report (should be sent to the topic adviser!)

== Topics ==

{| align="center" class="wikitable sortable" {{Prettytable}}
|-
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Prerequisites'''
|{{Hl2}} |'''Topic Advisor'''
|{{Hl2}} |'''Initial Readings'''
|-
| '''Title (assigned to )'''
| intro
| requirement
| [Shichang Ding--sding@gwdg.de]
| []
|-
| Visible Light Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Power Line Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Autonomous Driving: Principles, Standardization and Prospects
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| V2X Communications: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| QUIC Protocols: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| Smart Cities: Principles, Case Studies and Prospects in EU and Worldwide
| In this project, you will be devoted to solving specific prediction problems based on the given data. These tasks nowadays are common concerns for building smart cities in practice. Just enjoy the interaction with real-world data!
| Since we will solve some practical problems based on data engineering, I think a strong programming ability is necessary. Python as well as Keras or Tensowflow or PyTorch are always preferred. Don't hesitate to contact me if you feel interested and have preliminary knowledge in related projects. Let's work together!
| [Shuai Xu, shuai.xu@cs.uni-goettingen.de]
| [http://https://www.researchgate.net/publication/315871658_What_Your_Images_Reveal_Exploiting_Visual_Contents_for_Point-of-Interest_Recommendation],[https://arxiv.org/abs/1809.10770],[https://arxiv.org/abs/1811.02815],[https://arxiv.org/abs/1904.10322],[https://core.ac.uk/download/pdf/155789835.pdf]
|-
| Smart Grids: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Business Intelligence: Principles, Case Studies and Prospects
|
|
| [Yachao Shao, yshao@gwdg.de]
|-
| Logistics 4.0: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Digital Twin in Manufacturing: Principles, Standardization and Current Status in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Facial Recognition at Edge: Principles, Applications and Challenges
|
|
| [Xiaoming, xfu@gwdg.de]
|-
|}

==Workﬂow==

=== 1. Select a topic ===
A student picks a topic to work on. You can pick up a topic and start working '''at any time'''. However, make sure to notify the advisor of the topic before starting to work.

=== 2. Get your work advised ===
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

=== 3. Approach your topic ===

* By choosing a topic, you choose the direction of elaboration.
* You may work in different styles, for example:
** Survey: Basic introduction, an overview of the ﬁeld; general problems, methods, approaches.
** Specific problem: Detailed introduction, details about the problem and the solution.
* You should include your own thoughts on your topic.

=== 4. Prepare your presentation ===

* Present your topic to the audience (in English).
* 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the [http://www.net.informatik.uni-goettingen.de/ NET] group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation:
20 minutes are too short to present a topic fully.
It is alright to focus just on one certain important aspect.
Limit the introduction of basics.
Make sure to ﬁnish in time.

Suggestions for preparing the slides:
No more than 20 pages/slides.
Get your audiences to quickly understand the general idea.
Figures, tables and animations are better than sentences.
Summary of the topic: thinking in your own words.

=== 5. Write your report ===

* Present the problem with its background.
* Detail the approaches, techniques, methods to handle the problem.
* Evaluate and assess those approaches (e.g., pros and cons).
* Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

=== 6. Course schedule===
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the [[#Schedule]] to take appropriate actions.

[[Category:Courses]]

Seminar on Internet Technologies (Winter 2019 2020)

2019-09-18T18:38:50Z

Sxu: /* Topics */

== Details ==

{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and [http://134.76.18.81/?q=people/yachao-shao Yachao Shao]
|time=Oct 24'''''', 13:00ct: Introduction Meeting
|place=IFI Building, Room 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=242639&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
{{Announcement|Note:
we will have Introduction Meeting on the second week of new Winter Semester}}

==Course description==

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

==Passing requirements==
*There will be 2 milestones before the presentations where the students should pass before they register for the course.
**Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
**Midterm milestone. (ex. programming tasks done etc... )

*Actively and frequently participate in the project communication with your topic advisor
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentation + 10 min. Q&A).
** This accounts for 40% of your grade.
* Write a report on the selected topic (12-15 pages) (LaTeX Template:[ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip]).
** This accounts for 40% of your grade.
* Please check the [[#Schedule]] and adhere to it.

==Schedule==
* '''Oct. 24 16:00ct''': Introduction meeting
* '''Decemeber 20th ''' : Deadline for registration
* '''Jan. 6 and Jan. 7 2020''' : Presentations
* '''Mar. 31, 2020, 23:59''': Deadline for submission of report (should be sent to the topic adviser!)

== Topics ==

{| align="center" class="wikitable sortable" {{Prettytable}}
|-
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Prerequisites'''
|{{Hl2}} |'''Topic Advisor'''
|{{Hl2}} |'''Initial Readings'''
|-
| '''Title (assigned to )'''
| intro
| requirement
| [Shichang Ding--sding@gwdg.de]
| []
|-
| Visible Light Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Power Line Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Autonomous Driving: Principles, Standardization and Prospects
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| V2X Communications: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| QUIC Protocols: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| Smart Cities: Principles, Case Studies and Prospects in EU and Worldwide
| In this project, you will be devoted to solving specific prediction problems based on the given data. These tasks nowadays are common concerns for building smart cities in practice. Just enjoy the interaction with real-world data!
| Since we will solve some practical problems based on data engineering, I think a strong programming ability is necessary. Python as well as Keras or Tensowflow or PyTorch are always preferred. Don't hesitate to contact me if you feel interested and have preliminary knowledge in related projects. Let's work together!
| [Shuai Xu, shuai.xu@cs.uni-goettingen.de]
| [http://https://www.researchgate.net/publication/315871658_What_Your_Images_Reveal_Exploiting_Visual_Contents_for_Point-of-Interest_Recommendation]
|-
| Smart Grids: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Business Intelligence: Principles, Case Studies and Prospects
|
|
| [Yachao Shao, yshao@gwdg.de]
|-
| Logistics 4.0: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Digital Twin in Manufacturing: Principles, Standardization and Current Status in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Facial Recognition at Edge: Principles, Applications and Challenges
|
|
| [Xiaoming, xfu@gwdg.de]
|-
|}

==Workﬂow==

=== 1. Select a topic ===
A student picks a topic to work on. You can pick up a topic and start working '''at any time'''. However, make sure to notify the advisor of the topic before starting to work.

=== 2. Get your work advised ===
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

=== 3. Approach your topic ===

* By choosing a topic, you choose the direction of elaboration.
* You may work in different styles, for example:
** Survey: Basic introduction, an overview of the ﬁeld; general problems, methods, approaches.
** Specific problem: Detailed introduction, details about the problem and the solution.
* You should include your own thoughts on your topic.

=== 4. Prepare your presentation ===

* Present your topic to the audience (in English).
* 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the [http://www.net.informatik.uni-goettingen.de/ NET] group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation:
20 minutes are too short to present a topic fully.
It is alright to focus just on one certain important aspect.
Limit the introduction of basics.
Make sure to ﬁnish in time.

Suggestions for preparing the slides:
No more than 20 pages/slides.
Get your audiences to quickly understand the general idea.
Figures, tables and animations are better than sentences.
Summary of the topic: thinking in your own words.

=== 5. Write your report ===

* Present the problem with its background.
* Detail the approaches, techniques, methods to handle the problem.
* Evaluate and assess those approaches (e.g., pros and cons).
* Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

=== 6. Course schedule===
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the [[#Schedule]] to take appropriate actions.

[[Category:Courses]]

Seminar on Internet Technologies (Winter 2019 2020)

2019-09-18T18:35:18Z

Sxu: /* Topics */

== Details ==

{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and [http://134.76.18.81/?q=people/yachao-shao Yachao Shao]
|time=Oct 24'''''', 13:00ct: Introduction Meeting
|place=IFI Building, Room 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=242639&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
{{Announcement|Note:
we will have Introduction Meeting on the second week of new Winter Semester}}

==Course description==

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

==Passing requirements==
*There will be 2 milestones before the presentations where the students should pass before they register for the course.
**Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
**Midterm milestone. (ex. programming tasks done etc... )

*Actively and frequently participate in the project communication with your topic advisor
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentation + 10 min. Q&A).
** This accounts for 40% of your grade.
* Write a report on the selected topic (12-15 pages) (LaTeX Template:[ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip]).
** This accounts for 40% of your grade.
* Please check the [[#Schedule]] and adhere to it.

==Schedule==
* '''Oct. 24 16:00ct''': Introduction meeting
* '''Decemeber 20th ''' : Deadline for registration
* '''Jan. 6 and Jan. 7 2020''' : Presentations
* '''Mar. 31, 2020, 23:59''': Deadline for submission of report (should be sent to the topic adviser!)

== Topics ==

{| align="center" class="wikitable sortable" {{Prettytable}}
|-
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Prerequisites'''
|{{Hl2}} |'''Topic Advisor'''
|{{Hl2}} |'''Initial Readings'''
|-
| '''Title (assigned to )'''
| intro
| requirement
| [Shichang Ding--sding@gwdg.de]
| []
|-
| Visible Light Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Power Line Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Autonomous Driving: Principles, Standardization and Prospects
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| V2X Communications: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| QUIC Protocols: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| Smart Cities: Principles, Case Studies and Prospects in EU and Worldwide
| In this project, you will be devoted to solving specific prediction problems based on the given data. These tasks nowadays are common concerns for building smart cities in practice. Just enjoy the interaction with real-world data!
| Since we will solve some practical problems based on data engineering, I think a strong programming ability is necessary. Python as well as Keras or Tensowflow or PyTorch are always preferred. Don't hesitate to contact me if you feel interested and have preliminary knowledge in related projects. Let's work together!
| [Shuai Xu, shuai.xu@cs.uni-goettingen.de]
|-
| Smart Grids: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Business Intelligence: Principles, Case Studies and Prospects
|
|
| [Yachao Shao, yshao@gwdg.de]
|-
| Logistics 4.0: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Digital Twin in Manufacturing: Principles, Standardization and Current Status in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Facial Recognition at Edge: Principles, Applications and Challenges
|
|
| [Xiaoming, xfu@gwdg.de]
|-
|}

==Workﬂow==

=== 1. Select a topic ===
A student picks a topic to work on. You can pick up a topic and start working '''at any time'''. However, make sure to notify the advisor of the topic before starting to work.

=== 2. Get your work advised ===
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

=== 3. Approach your topic ===

* By choosing a topic, you choose the direction of elaboration.
* You may work in different styles, for example:
** Survey: Basic introduction, an overview of the ﬁeld; general problems, methods, approaches.
** Specific problem: Detailed introduction, details about the problem and the solution.
* You should include your own thoughts on your topic.

=== 4. Prepare your presentation ===

* Present your topic to the audience (in English).
* 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the [http://www.net.informatik.uni-goettingen.de/ NET] group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation:
20 minutes are too short to present a topic fully.
It is alright to focus just on one certain important aspect.
Limit the introduction of basics.
Make sure to ﬁnish in time.

Suggestions for preparing the slides:
No more than 20 pages/slides.
Get your audiences to quickly understand the general idea.
Figures, tables and animations are better than sentences.
Summary of the topic: thinking in your own words.

=== 5. Write your report ===

* Present the problem with its background.
* Detail the approaches, techniques, methods to handle the problem.
* Evaluate and assess those approaches (e.g., pros and cons).
* Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

=== 6. Course schedule===
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the [[#Schedule]] to take appropriate actions.

[[Category:Courses]]

Seminar on Internet Technologies (Winter 2019 2020)

2019-09-18T18:21:51Z

Sxu: /* Topics */

== Details ==

{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and [http://134.76.18.81/?q=people/yachao-shao Yachao Shao]
|time=Oct 24'''''', 13:00ct: Introduction Meeting
|place=IFI Building, Room 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=242639&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
{{Announcement|Note:
we will have Introduction Meeting on the second week of new Winter Semester}}

==Course description==

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

==Passing requirements==
*There will be 2 milestones before the presentations where the students should pass before they register for the course.
**Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
**Midterm milestone. (ex. programming tasks done etc... )

*Actively and frequently participate in the project communication with your topic advisor
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentation + 10 min. Q&A).
** This accounts for 40% of your grade.
* Write a report on the selected topic (12-15 pages) (LaTeX Template:[ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip]).
** This accounts for 40% of your grade.
* Please check the [[#Schedule]] and adhere to it.

==Schedule==
* '''Oct. 24 16:00ct''': Introduction meeting
* '''Decemeber 20th ''' : Deadline for registration
* '''Jan. 6 and Jan. 7 2020''' : Presentations
* '''Mar. 31, 2020, 23:59''': Deadline for submission of report (should be sent to the topic adviser!)

== Topics ==

{| align="center" class="wikitable sortable" {{Prettytable}}
|-
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Prerequisites'''
|{{Hl2}} |'''Topic Advisor'''
|{{Hl2}} |'''Initial Readings'''
|-
| '''Title (assigned to )'''
| intro
| requirement
| [Shichang Ding--sding@gwdg.de]
| []
|-
| Visible Light Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Power Line Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Autonomous Driving: Principles, Standardization and Prospects
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| V2X Communications: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| QUIC Protocols: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| Smart Cities: Principles, Case Studies and Prospects in EU and Worldwide
| intro
| intro2
| [Shuai Xu, shuai.xu@cs.uni-goettingen.de]
|-
| Smart Grids: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Business Intelligence: Principles, Case Studies and Prospects
|
|
| [Yachao Shao, yshao@gwdg.de]
|-
| Logistics 4.0: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Digital Twin in Manufacturing: Principles, Standardization and Current Status in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Facial Recognition at Edge: Principles, Applications and Challenges
|
|
| [Xiaoming, xfu@gwdg.de]
|-
|}

==Workﬂow==

=== 1. Select a topic ===
A student picks a topic to work on. You can pick up a topic and start working '''at any time'''. However, make sure to notify the advisor of the topic before starting to work.

=== 2. Get your work advised ===
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

=== 3. Approach your topic ===

* By choosing a topic, you choose the direction of elaboration.
* You may work in different styles, for example:
** Survey: Basic introduction, an overview of the ﬁeld; general problems, methods, approaches.
** Specific problem: Detailed introduction, details about the problem and the solution.
* You should include your own thoughts on your topic.

=== 4. Prepare your presentation ===

* Present your topic to the audience (in English).
* 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the [http://www.net.informatik.uni-goettingen.de/ NET] group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation:
20 minutes are too short to present a topic fully.
It is alright to focus just on one certain important aspect.
Limit the introduction of basics.
Make sure to ﬁnish in time.

Suggestions for preparing the slides:
No more than 20 pages/slides.
Get your audiences to quickly understand the general idea.
Figures, tables and animations are better than sentences.
Summary of the topic: thinking in your own words.

=== 5. Write your report ===

* Present the problem with its background.
* Detail the approaches, techniques, methods to handle the problem.
* Evaluate and assess those approaches (e.g., pros and cons).
* Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

=== 6. Course schedule===
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the [[#Schedule]] to take appropriate actions.

[[Category:Courses]]

Seminar on Internet Technologies (Winter 2019 2020)

2019-09-18T18:04:29Z

Sxu: /* Topics */

== Details ==

{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta=[http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and [http://134.76.18.81/?q=people/yachao-shao Yachao Shao]
|time=Oct 24'''''', 13:00ct: Introduction Meeting
|place=IFI Building, Room 2.101
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=242639&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
{{Announcement|Note:
we will have Introduction Meeting on the second week of new Winter Semester}}

==Course description==

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

==Passing requirements==
*There will be 2 milestones before the presentations where the students should pass before they register for the course.
**Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
**Midterm milestone. (ex. programming tasks done etc... )

*Actively and frequently participate in the project communication with your topic advisor
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentation + 10 min. Q&A).
** This accounts for 40% of your grade.
* Write a report on the selected topic (12-15 pages) (LaTeX Template:[ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip]).
** This accounts for 40% of your grade.
* Please check the [[#Schedule]] and adhere to it.

==Schedule==
* '''Oct. 24 16:00ct''': Introduction meeting
* '''Decemeber 20th ''' : Deadline for registration
* '''Jan. 6 and Jan. 7 2020''' : Presentations
* '''Mar. 31, 2020, 23:59''': Deadline for submission of report (should be sent to the topic adviser!)

== Topics ==

{| align="center" class="wikitable sortable" {{Prettytable}}
|-
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Prerequisites'''
|{{Hl2}} |'''Topic Advisor'''
|{{Hl2}} |'''Initial Readings'''
|-
| '''Title (assigned to )'''
| intro
| requirement
| [Shichang Ding--sding@gwdg.de]
| []
|-
| Visible Light Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Power Line Communications: Principles, Standardization and Applications
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Autonomous Driving: Principles, Standardization and Prospects
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| V2X Communications: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| QUIC Protocols: Principles, Standardization and Applications
|
|
| [Yali Yuan, yali.yuan@cs.uni-goettingen.de]
|-
| Smart Cities: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Shuai Xu, shuai.xu@cs.uni-goettingen.de]
|-
| Smart Grids: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Business Intelligence: Principles, Case Studies and Prospects
|
|
| [Yachao Shao, yshao@gwdg.de]
|-
| Logistics 4.0: Principles, Case Studies and Prospects in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Digital Twin in Manufacturing: Principles, Standardization and Current Status in EU and Worldwide
|
|
| [Xiaoming, xfu@gwdg.de]
|-
| Facial Recognition at Edge: Principles, Applications and Challenges
|
|
| [Xiaoming, xfu@gwdg.de]
|-
|}

==Workﬂow==

=== 1. Select a topic ===
A student picks a topic to work on. You can pick up a topic and start working '''at any time'''. However, make sure to notify the advisor of the topic before starting to work.

=== 2. Get your work advised ===
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

=== 3. Approach your topic ===

* By choosing a topic, you choose the direction of elaboration.
* You may work in different styles, for example:
** Survey: Basic introduction, an overview of the ﬁeld; general problems, methods, approaches.
** Specific problem: Detailed introduction, details about the problem and the solution.
* You should include your own thoughts on your topic.

=== 4. Prepare your presentation ===

* Present your topic to the audience (in English).
* 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the [http://www.net.informatik.uni-goettingen.de/ NET] group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation:
20 minutes are too short to present a topic fully.
It is alright to focus just on one certain important aspect.
Limit the introduction of basics.
Make sure to ﬁnish in time.

Suggestions for preparing the slides:
No more than 20 pages/slides.
Get your audiences to quickly understand the general idea.
Figures, tables and animations are better than sentences.
Summary of the topic: thinking in your own words.

=== 5. Write your report ===

* Present the problem with its background.
* Detail the approaches, techniques, methods to handle the problem.
* Evaluate and assess those approaches (e.g., pros and cons).
* Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

=== 6. Course schedule===
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the [[#Schedule]] to take appropriate actions.

[[Category:Courses]]

Advanced Computer Networks (Summer 2019)

2019-07-03T15:47:08Z

Sxu: /* Schedule (Tentative) */

== Details ==
{{CourseDetails
|credits=5ECTS
|module= M.Inf.1223.Mp OR 3.17: Selected Topics in Advanced Networking (ITIS)
|lecturer=[http://www.net.informatik.uni-goettingen.de/people/xiaoming_fu Prof. Xiaoming Fu], [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Dr. Mayutan Arumaithurai]
|ta= [http://www.net.informatik.uni-goettingen.de/people/sripriya%20srikant_adhatarao, Sripriya Srikant Adhatarao], [Shuai Xu]
|time=Thursdays, 10-12am.
|place=Rom:2.101
|univz=https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=231685&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&expand=0#auswahlBaum%7Cabschluss%3Aabschl%3D78%7Cstudiengang%3Astg%3D079%7CkontoOnTop%3Apordnr%3D361323%7Ckonto%3Apordnr%3D380740%7Ckonto%3Apordnr%3D384077%7Cveranst%3Averanstid%3D231685
}}

==Course description==
This lecture will introduce advanced concepts of computer networking to interested students. Topics include, but are not limited to:
*SDN and Cloud Computing
*Future Internet Technologies
*Big Data and Social Networking
*Machine Learning

For each topic, basic structures, features, applied techniques and security aspects will be taught. Additionally, each topic is accompanied with an exercise and it is mandatory to complete all the exercises to attend the final exam.

==Schedule (Tentative)==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''Date'''
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Lecturer'''
|{{Hl2}} |'''Lecture slides'''
|{{Hl2}} |'''Exercise/practice slides'''
|-
| align="right" | 18.04.2019
| Course Introduction and Information-Centric Networks I
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/0/04/0.CCN_I.pdf CCN-I][https://wiki.net.informatik.uni-goettingen.de/w/images/c/c9/0.CCN_II.pdf CCN-II]
|
|-
| align="right" | 25.04.2019
| Information-Centric Networks II
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/d/d8/SAID-ACN-final-delivered.pdf Congestion_control]
|
|-
| align="right" | 02.05.2019
| Exercise I: Information-Centric Networks
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/2/20/ICN_exercise.pdf Exercise I]
|
|-
| align="right" | 09.05.2019
| SDN I
| Osamah Barakat
|
|
|-
| align="right" |16.05.2019
| SDN II
| Osamah Barakat
|
|
|-
| align="right" | 23.05.2019
| Virtualization and Cloud Technologies
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 30.05.2019
| Holiday===NO LECTURE (PUBLIC HOLIDAY)
|
|
|
|-
| align="right" | 06.06.2019
| Exercise II: SDN + Cloud Computing
| Osamah Barakat
|
|
|-
| align="right" | 13.06.2019
| Big Data
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/19-BRmCbelv0ElOOXdtcJgQ-mqt2Gep9K/view?usp=sharing Slides]
|
|-
| align="right" | 20.06.2019
| Social Networks
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/14UwiN6Nqsf5V11vajsJLFm9UhUmfj_m6/view?usp=sharing Slides]
|
|-
| align="right" | 27.06.2019
| Machine Learning I
| Shichang Ding
|
|
|-
| align="right" |04.07.2019
| Machine Learning II
| Shuai Xu
|[https://drive.google.com/file/d/17f5A2iE81SbVwzoPVvGEZl3GUBgOGn4h/view?usp=sharing Slides]
|
|-
| align="right" | 11.07.2019
| Exercise III: Big Data+Social Networks+Machine Learning (or pratical course)
| Shichang Ding + Shuai Xu
|[https://drive.google.com/file/d/1rd86t2OHUjmlVd0uIFWLdc0HjfKAMwM8/view?usp=sharing Exercise III]
|
|-
| align="right" | 18.07.2019
| Written Examination (same time as the lecture. Room 2.101)
| Sripriya Adhatarao + Shuai Xu
|
|
|-
|}

==Prerequisites==
* Computer Science I, II; Computer Networks

[[Category:Courses]]

Advanced Computer Networks (Summer 2019)

2019-06-30T11:31:38Z

Sxu: /* Schedule (Tentative) */

== Details ==
{{CourseDetails
|credits=5ECTS
|module= M.Inf.1223.Mp OR 3.17: Selected Topics in Advanced Networking (ITIS)
|lecturer=[http://www.net.informatik.uni-goettingen.de/people/xiaoming_fu Prof. Xiaoming Fu], [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Dr. Mayutan Arumaithurai]
|ta= [http://www.net.informatik.uni-goettingen.de/people/sripriya%20srikant_adhatarao, Sripriya Srikant Adhatarao], [Shuai Xu]
|time=Thursdays, 10-12am.
|place=Rom:2.101
|univz=https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=231685&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&expand=0#auswahlBaum%7Cabschluss%3Aabschl%3D78%7Cstudiengang%3Astg%3D079%7CkontoOnTop%3Apordnr%3D361323%7Ckonto%3Apordnr%3D380740%7Ckonto%3Apordnr%3D384077%7Cveranst%3Averanstid%3D231685
}}

==Course description==
This lecture will introduce advanced concepts of computer networking to interested students. Topics include, but are not limited to:
*SDN and Cloud Computing
*Future Internet Technologies
*Big Data and Social Networking
*Machine Learning

For each topic, basic structures, features, applied techniques and security aspects will be taught. Additionally, each topic is accompanied with an exercise and it is mandatory to complete all the exercises to attend the final exam.

==Schedule (Tentative)==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''Date'''
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Lecturer'''
|{{Hl2}} |'''Lecture slides'''
|{{Hl2}} |'''Exercise/practice slides'''
|-
| align="right" | 18.04.2019
| Course Introduction and Information-Centric Networks I
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/0/04/0.CCN_I.pdf CCN-I][https://wiki.net.informatik.uni-goettingen.de/w/images/c/c9/0.CCN_II.pdf CCN-II]
|
|-
| align="right" | 25.04.2019
| Information-Centric Networks II
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/d/d8/SAID-ACN-final-delivered.pdf Congestion_control]
|
|-
| align="right" | 02.05.2019
| Exercise I: Information-Centric Networks
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/2/20/ICN_exercise.pdf Exercise I]
|
|-
| align="right" | 09.05.2019
| SDN I
| Osamah Barakat
|
|
|-
| align="right" |16.05.2019
| SDN II
| Osamah Barakat
|
|
|-
| align="right" | 23.05.2019
| Virtualization and Cloud Technologies
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 30.05.2019
| Holiday===NO LECTURE (PUBLIC HOLIDAY)
|
|
|
|-
| align="right" | 06.06.2019
| Exercise II: SDN + Cloud Computing
| Osamah Barakat
|
|
|-
| align="right" | 13.06.2019
| Big Data
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/19-BRmCbelv0ElOOXdtcJgQ-mqt2Gep9K/view?usp=sharing Slides]
|
|-
| align="right" | 20.06.2019
| Social Networks
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/14UwiN6Nqsf5V11vajsJLFm9UhUmfj_m6/view?usp=sharing Slides]
|
|-
| align="right" | 27.06.2019
| Machine Learning I
| Shichang Ding
|
|
|-
| align="right" |04.07.2019
| Machine Learning II
| Shuai Xu
|[https://drive.google.com/file/d/17f5A2iE81SbVwzoPVvGEZl3GUBgOGn4h/view?usp=sharing Slides]
|
|-
| align="right" | 11.07.2019
| Exercise III: Big Data+Social Networks+Machine Learning (or pratical course)
| Shichang Ding + Shuai Xu
|
|
|-
| align="right" | 18.07.2019
| Written Examination (same time as the lecture. Room 2.101)
| Sripriya Adhatarao + Shuai Xu
|
|
|-
|}

==Prerequisites==
* Computer Science I, II; Computer Networks

[[Category:Courses]]

Advanced Computer Networks (Summer 2019)

2019-06-20T09:22:07Z

Sxu: /* Schedule (Tentative) */

== Details ==
{{CourseDetails
|credits=5ECTS
|module= M.Inf.1223.Mp OR 3.17: Selected Topics in Advanced Networking (ITIS)
|lecturer=[http://www.net.informatik.uni-goettingen.de/people/xiaoming_fu Prof. Xiaoming Fu], [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Dr. Mayutan Arumaithurai]
|ta= [http://www.net.informatik.uni-goettingen.de/people/sripriya%20srikant_adhatarao, Sripriya Srikant Adhatarao], [Shuai Xu]
|time=Thursdays, 10-12am.
|place=Rom:2.101
|univz=https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=231685&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&expand=0#auswahlBaum%7Cabschluss%3Aabschl%3D78%7Cstudiengang%3Astg%3D079%7CkontoOnTop%3Apordnr%3D361323%7Ckonto%3Apordnr%3D380740%7Ckonto%3Apordnr%3D384077%7Cveranst%3Averanstid%3D231685
}}

==Course description==
This lecture will introduce advanced concepts of computer networking to interested students. Topics include, but are not limited to:
*SDN and Cloud Computing
*Future Internet Technologies
*Big Data and Social Networking
*Machine Learning

For each topic, basic structures, features, applied techniques and security aspects will be taught. Additionally, each topic is accompanied with an exercise and it is mandatory to complete all the exercises to attend the final exam.

==Schedule (Tentative)==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''Date'''
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Lecturer'''
|{{Hl2}} |'''Lecture slides'''
|{{Hl2}} |'''Exercise/practice slides'''
|-
| align="right" | 18.04.2019
| Course Introduction and Information-Centric Networks I
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/0/04/0.CCN_I.pdf CCN-I][https://wiki.net.informatik.uni-goettingen.de/w/images/c/c9/0.CCN_II.pdf CCN-II]
|
|-
| align="right" | 25.04.2019
| Information-Centric Networks II
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/d/d8/SAID-ACN-final-delivered.pdf Congestion_control]
|
|-
| align="right" | 02.05.2019
| Exercise I: Information-Centric Networks
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/2/20/ICN_exercise.pdf Exercise I]
|
|-
| align="right" | 09.05.2019
| SDN I
| Osamah Barakat
|
|
|-
| align="right" |16.05.2019
| SDN II
| Osamah Barakat
|
|
|-
| align="right" | 23.05.2019
| Virtualization and Cloud Technologies
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 30.05.2019
| Holiday===NO LECTURE (PUBLIC HOLIDAY)
|
|
|
|-
| align="right" | 06.06.2019
| Exercise II: SDN + Cloud Computing
| Osamah Barakat
|
|
|-
| align="right" | 13.06.2019
| Big Data
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/19-BRmCbelv0ElOOXdtcJgQ-mqt2Gep9K/view?usp=sharing Slides]
|
|-
| align="right" | 20.06.2019
| Social Networks
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/14UwiN6Nqsf5V11vajsJLFm9UhUmfj_m6/view?usp=sharing Slides]
|
|-
| align="right" | 27.06.2019
| Machine Learning I
| Shichang Ding
|
|
|-
| align="right" |04.07.2019
| Machine Learning II
| Shuai Xu
|
|
|-
| align="right" | 11.07.2019
| Exercise III: Big Data+Social Networks+Machine Learning (or pratical course)
| Shichang Ding + Shuai Xu
|
|
|-
| align="right" | 18.07.2019
| Written Examination (same time as the lecture. Room 2.101)
| Sripriya Adhatarao + Shuai Xu
|
|
|-
|}

==Prerequisites==
* Computer Science I, II; Computer Networks

[[Category:Courses]]

Advanced Computer Networks (Summer 2019)

2019-06-20T09:18:27Z

Sxu: /* Schedule (Tentative) */

== Details ==
{{CourseDetails
|credits=5ECTS
|module= M.Inf.1223.Mp OR 3.17: Selected Topics in Advanced Networking (ITIS)
|lecturer=[http://www.net.informatik.uni-goettingen.de/people/xiaoming_fu Prof. Xiaoming Fu], [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Dr. Mayutan Arumaithurai]
|ta= [http://www.net.informatik.uni-goettingen.de/people/sripriya%20srikant_adhatarao, Sripriya Srikant Adhatarao], [Shuai Xu]
|time=Thursdays, 10-12am.
|place=Rom:2.101
|univz=https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=231685&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&expand=0#auswahlBaum%7Cabschluss%3Aabschl%3D78%7Cstudiengang%3Astg%3D079%7CkontoOnTop%3Apordnr%3D361323%7Ckonto%3Apordnr%3D380740%7Ckonto%3Apordnr%3D384077%7Cveranst%3Averanstid%3D231685
}}

==Course description==
This lecture will introduce advanced concepts of computer networking to interested students. Topics include, but are not limited to:
*SDN and Cloud Computing
*Future Internet Technologies
*Big Data and Social Networking
*Machine Learning

For each topic, basic structures, features, applied techniques and security aspects will be taught. Additionally, each topic is accompanied with an exercise and it is mandatory to complete all the exercises to attend the final exam.

==Schedule (Tentative)==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''Date'''
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Lecturer'''
|{{Hl2}} |'''Lecture slides'''
|{{Hl2}} |'''Exercise/practice slides'''
|-
| align="right" | 18.04.2019
| Course Introduction and Information-Centric Networks I
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/0/04/0.CCN_I.pdf CCN-I][https://wiki.net.informatik.uni-goettingen.de/w/images/c/c9/0.CCN_II.pdf CCN-II]
|
|-
| align="right" | 25.04.2019
| Information-Centric Networks II
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/d/d8/SAID-ACN-final-delivered.pdf Congestion_control]
|
|-
| align="right" | 02.05.2019
| Exercise I: Information-Centric Networks
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/2/20/ICN_exercise.pdf Exercise I]
|
|-
| align="right" | 09.05.2019
| SDN I
| Osamah Barakat
|
|
|-
| align="right" |16.05.2019
| SDN II
| Osamah Barakat
|
|
|-
| align="right" | 23.05.2019
| Virtualization and Cloud Technologies
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 30.05.2019
| Holiday===NO LECTURE (PUBLIC HOLIDAY)
|
|
|
|-
| align="right" | 06.06.2019
| Exercise II: SDN + Cloud Computing
| Osamah Barakat
|
|
|-
| align="right" | 13.06.2019
| Big Data
| Prof.Dr. Xiaoming Fu
|[https://drive.google.com/file/d/19-BRmCbelv0ElOOXdtcJgQ-mqt2Gep9K/view?usp=sharing Slides]
|
|-
| align="right" | 20.06.2019
| Social Networks
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 27.06.2019
| Machine Learning I
| Shichang Ding
|
|
|-
| align="right" |04.07.2019
| Machine Learning II
| Shuai Xu
|
|
|-
| align="right" | 11.07.2019
| Exercise III: Big Data+Social Networks+Machine Learning (or pratical course)
| Shichang Ding + Shuai Xu
|
|
|-
| align="right" | 18.07.2019
| Written Examination (same time as the lecture. Room 2.101)
| Sripriya Adhatarao + Shuai Xu
|
|
|-
|}

==Prerequisites==
* Computer Science I, II; Computer Networks

[[Category:Courses]]

Advanced Computer Networks (Summer 2019)

2019-06-20T09:13:23Z

Sxu: /* Schedule (Tentative) */

== Details ==
{{CourseDetails
|credits=5ECTS
|module= M.Inf.1223.Mp OR 3.17: Selected Topics in Advanced Networking (ITIS)
|lecturer=[http://www.net.informatik.uni-goettingen.de/people/xiaoming_fu Prof. Xiaoming Fu], [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Dr. Mayutan Arumaithurai]
|ta= [http://www.net.informatik.uni-goettingen.de/people/sripriya%20srikant_adhatarao, Sripriya Srikant Adhatarao], [Shuai Xu]
|time=Thursdays, 10-12am.
|place=Rom:2.101
|univz=https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=231685&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&expand=0#auswahlBaum%7Cabschluss%3Aabschl%3D78%7Cstudiengang%3Astg%3D079%7CkontoOnTop%3Apordnr%3D361323%7Ckonto%3Apordnr%3D380740%7Ckonto%3Apordnr%3D384077%7Cveranst%3Averanstid%3D231685
}}

==Course description==
This lecture will introduce advanced concepts of computer networking to interested students. Topics include, but are not limited to:
*SDN and Cloud Computing
*Future Internet Technologies
*Big Data and Social Networking
*Machine Learning

For each topic, basic structures, features, applied techniques and security aspects will be taught. Additionally, each topic is accompanied with an exercise and it is mandatory to complete all the exercises to attend the final exam.

==Schedule (Tentative)==
{| {{Prettytable|width=}}
|-
|{{Hl2}} |'''Date'''
|{{Hl2}} |'''Topic'''
|{{Hl2}} |'''Lecturer'''
|{{Hl2}} |'''Lecture slides'''
|{{Hl2}} |'''Exercise/practice slides'''
|-
| align="right" | 18.04.2019
| Course Introduction and Information-Centric Networks I
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/0/04/0.CCN_I.pdf CCN-I][https://wiki.net.informatik.uni-goettingen.de/w/images/c/c9/0.CCN_II.pdf CCN-II]
|
|-
| align="right" | 25.04.2019
| Information-Centric Networks II
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/d/d8/SAID-ACN-final-delivered.pdf Congestion_control]
|
|-
| align="right" | 02.05.2019
| Exercise I: Information-Centric Networks
| Mayutan Arumaithurai
| [https://wiki.net.informatik.uni-goettingen.de/w/images/2/20/ICN_exercise.pdf Exercise I]
|
|-
| align="right" | 09.05.2019
| SDN I
| Osamah Barakat
|
|
|-
| align="right" |16.05.2019
| SDN II
| Osamah Barakat
|
|
|-
| align="right" | 23.05.2019
| Virtualization and Cloud Technologies
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 30.05.2019
| Holiday===NO LECTURE (PUBLIC HOLIDAY)
|
|
|
|-
| align="right" | 06.06.2019
| Exercise II: SDN + Cloud Computing
| Osamah Barakat
|
|
|-
| align="right" | 13.06.2019
| Big Data
| Prof.Dr. Xiaoming Fu
|[https://wiki.net.informatik.uni-goettingen.de/w/images/2/20/1.pdf Slides]
|
|-
| align="right" | 20.06.2019
| Social Networks
| Prof.Dr. Xiaoming Fu
|
|
|-
| align="right" | 27.06.2019
| Machine Learning I
| Shichang Ding
|
|
|-
| align="right" |04.07.2019
| Machine Learning II
| Shuai Xu
|
|
|-
| align="right" | 11.07.2019
| Exercise III: Big Data+Social Networks+Machine Learning (or pratical course)
| Shichang Ding + Shuai Xu
|
|
|-
| align="right" | 18.07.2019
| Written Examination (same time as the lecture. Room 2.101)
| Sripriya Adhatarao + Shuai Xu
|
|
|-
|}

==Prerequisites==
* Computer Science I, II; Computer Networks

[[Category:Courses]]