Tools#

Google Colab#

For in-class exercises and tutorials we will be using Jupyter notebooks, an interactive web-based interface combining narrative text and live code you can tweak and run yourself.

The backend to streamline this is called a JupyterHub, a multi-user server designed to support many users by managing singular Jupyter Notebook servers.

 

../_images/jupyter_nb_df_demo.gif

 
 

The exercises and programming practice for this course will be done on Colaboratory, Google’s online front end interface from its cloud. Datasets on GDrive can be accessed via a Jupyter Notebook on Colab.

Large Language Models & AI assistants#

It can be very tempting to surrender too soon with those mindboggling Large Language Models! On the one hand, they can generate clean, well-structured code that follows best practices. On the other hand, they provide instant access to answers: the joy — usually after frustrations and confusion — of figuring things out on your own is completely missed, along with the true learning opportunity that comes with it.

This course will give tips on how to get the best out of AI tools, avoiding the risk of becoming over-reliant while benefiting from their true educational power.