/Lecture_AI_in_Automotive_Technology

This is the github Repository that belongs to the lecture "Artificial Intelligence in Automotive Technology" from the Institute of Automotive Technology of the Technical University of Munich

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

TUM Course "Artificial Intelligence in Automotive Technology"

This is the Github repository that belongs to the course "Artificial Intelligence in Automotive Technology" from the Institute of Automotive Technology of the Technical University of Munich.

In this repository we will upload the practice session material that belongs to each of the 13 lectures that will teach you the foundations of Artificial Intelligence with regard to its use in automotive technology. Beside the lecture material, that you can find on our main course website, we will upload here the coding examples we were using in the practice session of each lecture. In addition to the coding material you will find a video for each practice session after the regular lecture in the youtube video.

Lecture Overview:

  1. Lecture 1 - Introduction: Artificial Intelligence - https://youtu.be/f_VvScVwBGU (Practice session start time: 1:11:28)
  2. Lecture 2 - Computer Vision - https://youtu.be/9fTCZ1QPLIg (Practice session start time: 1:26:34)
  3. Lecture 3 - Supervised Learning: Regression - https://youtu.be/kgOessQts_Q (Practice session start time: 1:28:17)
  4. Lecture 4 - Supervised Learning: Classification - https://youtu.be/Ow_q7htvo-8 (Practice session start time: 1:22:45)
  5. Lecture 5 - Unsupervised Learning: Clustering - https://youtu.be/eVpsqvdZrTE (Practice session start time: 1:22:00)
  6. Lecture 6 - Path Finding: From British Museum to A* - https://www.youtube.com/watch?v=d5lyM2or8cs (Practice session start time: 1:32:30)
  7. Lecture 7 - Introduction Neuronal Networks - https://www.youtube.com/watch?v=ksxzoG5YktY (Practice session start time: 1:35:55)
  8. Lecture 8 - Deep Neural Networks - https://www.youtube.com/watch?v=T3kQLnWpeCg (Practice session start time: 1:14:58)
  9. Lecture 9 - Convolutional Neuronal Networks - https://www.youtube.com/watch?v=3YccAgMwgRM (Practice session start time: 1:29:45)
  10. Lecture 10 - Recurrent Neuronal Networks - https://www.youtube.com/watch?v=wX4qozViCnI&t=249s (Practice session start time: 1:15:30)
  11. Lecture 11 - Reeinforcement Learning - https://www.youtube.com/watch?v=aGmVbAlicw0 (Practice session start time: 1:29:30)
  12. Lecture 12 - AI-Development
  13. Lecture 13 - Guest Lecturer Rasmus Rothe