Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses.
- 5 stars60.82%
- 4 stars27.79%
- 3 stars8.24%
- 2 stars2.01%
- 1 star1.11%
Good course - I'm now confident to oversee an end-to-end data science experiment. Some interactivity would make this the perfect overview of data science.
Exceptional course in conveying a real life situation, vastly different from an ideal one. The course puts you up to speed in handling such situations with aplomb.
I like that this course examples the many ways an experiment/analysis can go wrong and how to address these issues. Very practical for the practitioner.
Another excellent Executive Data Science course. Brian gives clear and concise explanations of the ideal versus real world of the data science workplace.