Connect as follows:

1. Learn/review how to use the TACC Analysis Portal.
2. Login to the TACC Analysis Portal.
3. Select session settings. Unless instructed otherwise for specific labs, we recommend:
   • System: Frontera
   • Application: Jupyter notebook
   • Project: Any of your allocation(s)
   • Queue: Frontera: rtx-dev, rtx
   • Nodes: 1
   • Tasks: 1
   • Time Limit: the TAP default runtime of 2 hours is usually sufficient to complete the lab
   • Reservation: the reservation in which to run the job. You may have access to a reservation if you are using these materials as part of a class
4. After selecting your session settings, <Submit>
5. On the next screen, choose <Connect> when it is available.
6. You will then be in the Jupyter Notebook Dashboard. From the Dashboard, you can navigate through your TACC filesystem, and can launch an existing or new Jupyter notebook. If Jupyter notebooks are new to you, you can learn/review how to use them in a sandbox environment.

The lab exercise files for the Chishiki-AI Classification and CNN courses can be downloaded from GitHub directly into your TACC file space. After you have started your TAP session, select Terminal from the New dropdown list. At the prompt, copy the files to your $HOME folder:

All lab exercises are run in a container through TACC Apptainer. A container is an environment that contains all the software and libraries needed to run the lab, and you will not need to install any Python packages yourself. After you have started your TAP session, select Terminal from the New dropdown list. At the prompt, copy and run the container installation script:

Be sure to test your if installation is successful. Refresh your TAP session home page and select cnn_course_container from the New dropdown list. It opens a blank Jupyter notebook with Kernel starting, please wait... text displayed to the left of the kernel/container name, cnn_course_container. Once the kernel is ready, you will just see the kernel name and the installation is successful.