The Machine Learning & AI course is one of two elective courses on the 1./2. semester of the Bachelor programme at Cphbusiness/Lyngby SOFT. It is taught this semester (2019, spring) by Jens Egholm Pedersen (JEEP) and Jacob Trier Frederiksen (JTF).

• General information on the courses of spring 2019 semester is on GitHub here:

  • https://datsoftlyngby.github.io/soft2019spring/

• Specific information on ML & AI course is on GitHub here:

  • https://datsoftlyngby.github.io/soft2019spring/AI_plan.html

• Course books:

  • 100 page ML book: http://themlbook.com/wiki/doku.php
  • Hands-on ML with Scikit-Learn, Keras and Tensorflow: https://github.com/ageron/handson-ml2

• Course work material is on GitHub, here:

  • https://github.com/datsoftlyngby/soft2019spring-ai

We shall use the following resource infrastructure:

• We will use the courses' Moodle Flow for announcements to the class.

• Will be used extensively for relaying course materials, so link it in.

• All hand-in assignments are subject to peer review (you "grade" your fellow students), and will be conducted through Peergrade. You will receive information from us on how to sign up and participate in due time.

• For active participation during class hours, we shall use the peer participation tool Mentimeter:. You will receive instructions from us in due time, during the course when active participation is warranted (or required).

There exists a ton of resources that helps you understand the material. Be proactive: find the video/books/games/friends that helps you learn! We added some resources to things that might help you: