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.
About this Course
Skills you will gain
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
- 5 stars60.82%
- 4 stars27.76%
- 3 stars8.26%
- 2 stars2.02%
- 1 star1.11%
TOP REVIEWS FROM DATA SCIENCE IN REAL LIFE
Gives directions on how to deal with a situation where a clear conclusion may not be forthcoming from the analysis--- a situation that more often than not is likely to hold true in real world
Another excellent Executive Data Science course. Brian gives clear and concise explanations of the ideal versus real world of the data science workplace.
Examples used in this course are related to Lifescience and candidates like me find it difficult to correlate. It would be beneficial to use some common life examples.
It was kind of hard to understand as I did not have any professional experience in data science. But, I am sure I can work in a professional environment now with the teachings of the professor.
About the Executive Data Science Specialization
Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.
Frequently Asked Questions
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