AI/ML Course Week 1

Announcements:

Welcome AI/ML Course Students: The AI/ML Course is a standalone course available in addition to the Main ABCD-ReproNim Course. You can find the AI/ML Course syllabus here. If you haven’t already, please make sure to register here so we can add you to our AI/ML Course email list! Please note: we recommend that students first complete the Main Course before beginning the AI/ML Course. AI/ML Course materials will be updated weekly and will remain online indefinitely.

Week 1 AI/ML Data Exercise: Each week we will ask AI/ML Course students to complete a Data Exercise about the week’s lectures. Please complete the Week 1 AI/ML Data Exercise after viewing the Week 1 AI/ML videos. Solutions for this week’s data exercise can be found on our GitHub

ABCD Data Access Confirmation: If you wish to access ABCD data you will need an active Data Use Certification (DUC) from the NDA. We provide instructions on how to obtain ABCD data access to help with this process. Once you have an approved DUC please complete our ABCD Data Access Confirmation. Note that you do not need to have ABCD data access in order to take the AI/ML Course. This assignment is optional and does not count towards completion of the course. However, students who do not successfully complete this assignment will not be allowed to participate in Project Month.

ABCD-ReproNim JupyterHub Access Request: ABCD-ReproNim students with active DUCs can access to the new ABCD-ReproNim JupyterHub, a cloud-based scientific computing platform that is fully accessible through an internet browser (see this link for details about the JupyterHub project!) This document introduces the ABCD-ReproNim JupyterHub, how to access it, and outlines some basic usage rules. Students can use the Hub to work on Data Exercises and perform ABCD data analysis projects during the course. ABCD-ReproNim staff will grant access to students with active DUCs who submit an Access Request. Students without an active NDA Data Use Certification are invited to follow the instructions here where they can access the same computational environment locally via Docker.