A few weeks I got to speak at PyDataCambridge (thanks for having me!), slides are here for “On The Delivery of Data Science Projects“.
This talk is based on my experiences coaching teams (whilst building IP for clients) to help them derisk, design and deliver working data science products. This talk is really in two halves – it takes the important lessons from my two training classes and boils them down into a 30 minute talk. We cover:
- What makes for a successful data science project?
- Developing a Project Specification for shared agreement including a Definition of Done
- Using standard tools and processes to standardize and simplify
- Ideas around best practice
Let me know if you found this talk useful? I really think the ideas around successful project delivery need to be collected and shared, we’re still in the “wild west” and I’m keen to collate more examples of successful process.
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.