Training Courses for 2020 Q1 – Successful Data Science Projects & Software Engineering for Data Scientists

Early next year I run new iterations of two of my existing training courses for Pythonic Data Scientists:

Successful Data Science Projects focuses on reducing uncertainty in a new data science project. We’ll look at the reasons why these projects can fail (and heck – this is research – they can and occasionally should fail), review ways to derisk a project with tools you’re probably not yet using, plan out a Project Specification for agreement with stakeholders and review techniques to make your team more highly performant overall.

“After attending the course I can identify and communicate to the project team and client the uncertainties of the project efficiently. I am using the techniques covered on the course to write project initiation documents and put in place the necessary processes to reduce uncertainty. The course was very engaging and I was very happy to learn from Ian’s experience to ensure a successful delivery on all future projects.” – Dani Papamaximou, Data Scientist at Arcadia

Software Engineering for Data Scientists is a 2 day course aimed at data scientists (perhaps from an academic background) who lack strong software engineering skills. We cover reviewing “bad Notebook code”, refactoring this code, using a standardised folder structure (with cookiecutter), adding unit tests and defensive Pandas tests along with checking how to introduce these techniques back into your team.

“Ian’s Software Engineering for Data Scientists course provides an excellent overview of best practices with focus on testing, debugging and general code maintenance. Ian has a wealth of experience and also makes sure to keep on top of the latest tools and libraries in the Data Science world. I would especially recommend the course to Data Science practitioners coming from an academic rather than software engineering background.” – LibertyGlobal Mirka

I am also thinking of introducing a High Performance Python course based on the updates coming to the 2nd edition of my High Performance Python book (for release April 2020). You’ll get details about this on my low-frequency email training list and if you have strong thoughts about this, please get in contact!

Ian is a Chief Interim Data Scientist via his Mor Consulting. Sign-up for Data Science tutorials in London and to hear about his data science thoughts and jobs. He lives in London, is walked by his high energy Springer Spaniel and is a consumer of fine coffees.