Software Engineering for Data Scientists (September) - write stronger research code, refactor to make it maintainable, add unit tests and defensible data loading tests so you trust your processing. You'll gain confidence in your coding, this is especially powerful if you lack a formal software engineering background.
Higher Performance Python (October) - learn to profile slow & memory hogging code including Pandas and sklearn, learn to compile using Numba and to parallelise to multi-core with Dask. You'll speed-up numeric code by 200*, massively increase the speed of some of your Pandas operations and you'll understand how to handle "bigger than RAM datasets" in Pandas.
Successful Data Science Projects runs in November, we'll work through how to estimate the value of a project, derisk it, design a project and develop a defensible project specification to improve the value and likelihood of your delivery. This course also covers leadership training.
Join the low-volume course announce list (click the button below) to hear when these courses are given dates and to get early-access to the discounted early-bird tickets.