If you’re learning data science, you have at some point come across RStudio, iPython, Jupyter or some other form of “interactive” learning portal. You’ve learned how to produce data science work in a notebook format – and you wonder if real-world data science has more to it than interactive notebooks.
In this workshop, corporate trainer and consultant Samuel Chan will walk us through his daily routine and process: on how he brings his work out of a “development” mode into “production” mode, how we deliver corporate projects, what he thinks about solution-centric and impact-based data science.
We’ll explore the “gotchas”, the best practices of building machine learning features, the blurry line between machine learning code and software engineering, and how to stay laser-sharp on devising impact-driven solutions with AI.
The workshop and all workshop materials are developed / conducted in English. It is suitable for the general public – no programming experience is required.
The goal is to turn data into information, and information into insight. ~ Carly Fiorina, former CEO of Hewlett-Packard