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Another Successful Data Science Projects course completed

A week back I ran the 4th iteration of my 1 day Successful Data Science Projects course. We covered: How to write a Project Specification including a strong Definition of Done How to derisk a new dataset quickly using Pandas Profiling, Seaborn and dabl Building interactive data tools using Altair to identify trends and outliers […]

Higher Performance Python (ODSC 2019)

Building on PyDataCambridge last week I had the additional pleasure of talking on Higher Performance Python at ODSC 2019 yesterday. I had a brilliant room of 300 Pythonic data scientists at all levels who asked an interesting array of questions: This talk expanded on last week’s version at PyDataCambridge as I had some more time. […]

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 (Jan, 1 day) Software Engineering for Data Scientists (Feb, 2 day) Successful Data Science Projects focuses on reducing uncertainty in a new data science project. We’ll look at the reasons why these projects […]

Thoughts on how to start a PyData or Python meetup

At PyConLT 2019 (Lithuania) we just had a 10-person meeting on “how to start a new PyData or Python meetup” with existing organisers and some potential new event organisers. The night before in the conference bar Radovan and I had spent an hour helping someone from Latvia figure out their plan to start a new […]

Second Successfully Delivering Data Science Projects just over

I ran the second iteration of my Successfully Delivering Data Science Projects course last Friday to this happy group, we had a lovely day and good conversation has continued in the teaching slack over the weekend: Topics covered included the design and derisking of data projects (not just machine learning), building a project plan, communicating […]