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Zoom meetings links for Hybrid Online teaching in Winter Semester 2021/22

As you are all well aware of the current global situation regarding COVID-19 (Coronavirus SARS-CoV-2), we will be unable to have face to face lectures at the moment. This however, does not mean that your education has to suffer. We have used the current technologies available to us to ensure that we can have online lectures for you throughout the time that we are unable to meet face to face. You will find the instructions regarding all of your courses on this page.

We will keep this page updated so that you can get the information that you need regarding which "room" to go to for your lectures.

We look forward to "seeing" you soon.

Hardware Requirements for attending online lectures

  • 0: Computer/Laptop.
  • 1: Microphone.
  • 2: Webcam. We recommend that you turn your webcam on during the lectures since it makes the experience more interactive when you can see the people who are in the lecture with you. If you do not have a webcam you can stream the video output of your phone directly to your computer using DroidCam, Install instructions can be found https://www.dev47apps.com/
  • 3: Optional/Recommended: A graphics tablet. This will be useful for when you want to discuss ideas with your teachers or have discussions amongst yourselves.

Instructions for Setting up Zoom

  • Step 1: Open www.zoom.us.
  • Step 2: Click on Signup for free.
  • Step 3: Provide your date of birth.
  • Step 4: Provide your university email id.
  • Step 5: You will receive an email to the given email id for activating your account.
  • Step 6: Join your account with the uni-hidlesheim's rechenzentrum.
  • Step 7: Enter you First Name, Last Name and password details.
  • Step 8: Skip inviting any colleagues.
  • Step 9: You have a zoom account and ready to attend the webinars virtually.
  • Step 9.5: Some lectures might require you to register your account for that meeting before you can participate. If that is the case, a registration link is posted besides the lecture.
  • Step 10: In order to attend an online lecture you will need the Meeting ID, these can be found in the table named "Online Courses for Summer Semester 2020" .

Online Courses for Winter Semester 2021

Course Zoom Meeting ID Time Registration Link
Deep Learning Lab 8827 1768 5818 Wed. 14:00 - 18:00 Register
Einfuehrung in die Informatik - Lecture 850 2417 7736 Tue. 14:15-15:45 Register

Math Precourse 6th-9th April

Course Zoom Meeting ID Time
Math Precourse 884 2909 0538 9:00-12:00

Online Courses for Summer Semester 2021

Course Zoom Meeting ID Time Registration Link
Machine Learning 2 - Lecture 819 6381 9064 Fri. 10:15-12:00 Register
Machine Learning 2 - Tutorial G1 830 3231 0195 Tue. 08:15-10:00
Machine Learning 2 - Tutorial G2 823 5418 4186 Wed. 14:15-16:00
Machine Learning 2 - Tutorial G3 852 3540 6497 Fri. 08:00-10:00
Deep Learning - Lecture 913-8168-0462 Tue. 10:15-12:00
Deep Learning - Tutorial G1 813 3111 5925 Fri. 12:15-14:00
Big Data Analytics - Lecture 825 4839 9227 Mon. 10:15-12:00
Big Data Analytics - Tutorial G1 857 0148 1144 Thu. 08:15-10:00
Big Data Analytics - Tutorial G2 821 1727 9415 Thu. 14:15-16:00
DA Seminar 1 833 1785 1191 Tue. 14.15-16.00
DA Seminar 2 882 0794 0444 Tue. 14.15-16.00
DA Seminar 3 840-8360-0439 Tue. 14.15-16.00
Lab: Distributed Data Analytics G1 863-9352-6671 Mon. 14.15-16.00
Lab: Distributed Data Analytics G2 884-5209-9122 Thurs. 12.15-14.00
Oberseminar 914-6451-8489 Tue. 18.00-20.00

Student Research Project Meetings

Event Zoom Meeting ID Date Time
SRP First Interim Presentation 861-6183-7423 03.06.2020 Wed. 14.00-18.00
SRP 2nd Interim Presentation (day 1) registration link 08.10.2020 Th. 14.00-18.00
SRP 2nd Interim Presentation (day 2) registration link 09.10.2020 Fr. 9.00-13.00

Online Courses for Winter Semester 2020

Course Zoom Meeting ID Time
Machine Learning - Tutorial 4 872 2462 3202 W 14.00-16.00
Machine Learning - Tutorial 3 812 4043 7688 W 8.00-10.00
Machine Learning - Tutorial 2 837 2708 7318 T 8.00-10.00
Machine Learning - Tutorial 1 876 7773 1179 M 8.00-10.00
Machine Learning Precourse - Lecture 886 4598 7696 M-F 9.00-12.00
Machine Learning - Lecture 831 2488 8997 Fri. 10.00-12.00
Modern Optimization Techniques - Lecture 899 1589 4085 Tue. 10.00-12.00
Modern Optimization Techniques - Tutorial G1 869 6081 6289 Tue. 08.00-10.00
Modern Optimization Techniques - Tutorial G2 8845 0119 6900 Wed. 14.00-16.00
Planning and Optimal Control - Lecture 839 3379 0960 Tue. 10.00-12.00
Planning and Optimal Control - Tutorial G1 876 9375 7790 Thu. 08.00-10.00
Planning and Optimal Control - Tutorial G2 882 4705 5965 Fri. 12.00-14.00
Lab: Programming Machine Learning G1 890 5738 8611 Mon. 14.15-16.00
Lab: Programming Machine Learning G2 848 7170 8903 Thurs. 10.15-12.00
Lab: Deep Learning 859 0698 7429 Wed. 14.15-18.00
Seminar 1 870 8810 0523 Tue. 14.15-16.00
Seminar 2 838 4849 4082 Tue. 14.15-16.00
Seminar 3 861-9121-4795 Tue. 14.15-16.00
Oberseminar 914-6451-8489 Tue. 18.00-20.00