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Advanced Time Series Prediction

Hi everybody......it´s Kristian - your course instructor. I will guide you through the "Advanced Time Series Prediction"-course this semester.

Welcome to all participants.

We start with a short introduction of the course topics. Get to know each other and explain the course structure and all the required tasks for a successful participation.

This requires i.e.: Give a project presentation and provide a well documented code with data via GitHub. Addtionally you are only allowed to miss two class sessions during the semester.

Requirements for a Certificate of Achievement or ECTS

The conditions to be met in order to receive a Certificate of Achievement (and ECTS) are:

Attendance to at least 80% of the classes (it is allowed to miss maximum 2 times)
Delivery of a ML-Time Series project and including the needed documentation (GitHub-repository is recommended)
Upload of your presentation (PDF-file is preferred) to the Edu-Campus-System

Attendance:

If you attend via Zoom, please make sure to use your full name, which should be the same that you used to register at edu.opencampus.sh. Otherwise your attendance will not be recorded!

Please switch on your camera - ask questions - be (inter)-active!!

Projects:

Check the Projects section to learn more about the projects.

Projects & Frameworks

Here we present some potential project ideas:

For the semester project - you can bring your own data - we will discuss this in the first/second session. Nevertheless here you can find some resources to think about a potential project:

Check out these frameworks:

Lecture material + YouTube

For the summer-term 2024 we use mainly YouTube playlists and freely available resources.

Check out the more detailed playlists in each week.

In case you enjoy Coursera - here are some suggestions:

register with Google and the Coursera platform to get corresponding accounts. Since we switched for the second/third run our video lecture sources (the Coursera part is optional - but still benefical for the interested) this part is optional.

Please enroll/attend/complete the following Coursera MOOCs during the semester:

References / Books

YES.....books.....you may heard about it....these things were used in former times ;-)

Last but not least - here are some very good book references. It is not required or requested to buy any of these books. If you are enrolled as a student at CAU, FH Kiel or another university you might have access to these books via the SpringerLink of your home institution. They cover the course material quite well and provide GitHub-Repositories for the codes which where used throughout the book. Unfortunately there is no 1:1-Coursera course matching these books perfectly - but we will do our best ;-)