Throughout the semester, we may need a few datasets for our hands-on tutorial sessions as well as assignments. All the data we use in class are available on the Dropbox drive. Please download the data from the following link as a zipped file and unzip the data to your working directory. (NB: The data is limited to enrolled students only. Please ask the instructor for the access code.)
It is highly recommended that you create a
Working_Directory
to save all the course materials. Under
your working directory, you place the unzipped
ENC2045_demo_data
directory. Also under your
Working_Directory
are all the notebook files you create for
the tutorials and assignments.
With the above file structure, if you want to access a particular
file in the demo_data
in your jupyter notebook, you may
access it using the following path:
Path_to_Your_Working_Directory/ENC2045_demo_data/dataset1.csv
demo_data/dataset1.csv
A final note is that it is strongly recommended to always set your
working directory of the jupyter notebook to your
Working_Directory
before you run the scripts.
We will also use Google
Colab to run the notebooks during the class sessions (esp. for tasks
that require GPU computing). We assume that you have downloaded all the
necessary datasets onto your Google Drive
(Your_Google_Drive_Root/ENC2045_demo_data/
). When executing
the notebook on Google Colab, we can mount the Google Drive and access
necessary files directly from Google Drive.
A few more suggestions regarding the naming of the files and directories:
_
)The above principles should apply to all the intermediate directories
on the path that lead to your Working_Directory
. Sticking
to these principles will definitely make your life much easier. Please
trust me.