Short Course: Data Science for Industry
"Data Science for Industry" provides an applied, hands-on introduction to selected topics useful in the working world of data science. Broadly these topics fall into two themes: workflow/productivity tools and skills (GitHub, data wrangling, visualization, Shiny applications) and modelling (recommender systems, text mining, neural networks). The short course is an abbreviated version of the module of the same name offered in the MSc Data Science program at the University of Cape Town, covering a selection of the topics. Much of the material covered in the course is available at https://github.com/iandurbach/datasci-fi.
The course consists of 6 lectures, taking place on Monday, Wednesday and Friday 4 – 6:30pm for two weeks, starting 29 July 2019. Most of these lectures are in traditional lecture format, but some take the format of a practical/tutorial. In these you would be expected to work through a video lecture before the class meeting, with the lecture time being used for computer practicals and discussion.
Material to be covered:
Monday 5 August: Data wrangling, workflow, R projects, R markdown, Git and GitHub
Wednesday 7 August: Recommender systems
Thursday 8 August: Neural networks I, cloud computing with Amazon Web Services
Monday 12 August: Text analytics
Wednesday 14 August: Shiny apps, making R packages
Friday 16 August: Neural networks II
The course is conducted in R and you should already have at least a working knowledge of R (e.g. reading in data, running basic statistical analyses). Most classes are partially interactive and so having your own laptop, while not essential, will be a benefit.
A certificate of completion will be issued upon successful completion of the course, including completing a small assignment/exercise.
For more information email email@example.com.
To apply for a place on the short course, please complete the application form at https://goo.gl/forms/Nf64RKLz0UvP62243
Applications close 1 July but as limited places are available you are advised to apply as early as possible.