Code for Living (Python for Data Engineering)
Thu, 17th November | 18:00 - 20:30 GMT (GMT+00:00)

In this session we’ll be taking a look at harnessing the power of data to aid decision making for things like groceries and everyday purchases. We’ll get hands on with sourcing and making sense of the data, and then using it to answer some interesting questions, using techniques from fields like optimisation and machine learning.

The agenda is as follows:

• Short introduction presentation by Compare The Market
• Workshop
• Getting set up and started with the notebooks
• Loading in and exploring the pricing dataset (pandas, with an option for sql)
• Using/querying the data to answer questions such as ‘What is the cheapest place to shop for a given shopping basket?’
• Adding in the nutrition dataset and using it to answer questions around finding healthier, cheaper alternatives.
• Setting up, training and testing a small model to label items and find alternatives/similar items. (tensorflow/keras/scikit-learn)

Requirements:

• A google account - we will be using google collab, a web based jupyter notebook to run the workshop. Alternatively, you can download jupyter/anaconda locally - make sure to have git installed as well if so.
• Your laptop!
• Some basic familiarity with Python would be nice to have, and SQL knowledge is optional.
• Join the codebar ctm-python-workshop Slack channel to keep up to date with information before and during the event.

If you have any questions ahead of the workshop please drop an email to [email protected].