This is a short popular science introduction course to Artificial Intelligence. All lecture materials can be found in the course Github repo.
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For detailed time schedule click here
| Week | Content |
|---|---|
| 33 | intro, concepts, AI workflow |
| 34 | history, markdown |
| 35 | seminar (monday), report (friday) |
The reading and video resources in this course are mostly for getting an overview and understanding of the field. They can be used as reference material for your seminar and for the voluntary report. These resources are by far not complete and you are encouraged to search for materials.
Week 33
Lecture
Videos 📹
Articles 📰
Week 35
Video guides 📹
Articles 📰
Some fundamental steps of the machine learning workflow can be found below, but you should also find more detailed materials in each step for your report.
Example of technologies used in a machine learning workflow. Note that there can be more, less or different technologies in the technology stack depending on a projects need and requirements.