When you think of what data scientists do on a daily basis, you probably think of working with data. Yet data scientists typically derive insights on behalf of their organization or for a client, so any insights they obtain from their data need to be accessible to a broader audience. Often, that audience is less familiar with —or even uncomfortable with —data analysis or statistics. For this reason, communication is just as important to a data scientist's success as working with data.
In this course, you will explore the process of working with a client to understand their data science needs and provide them with a summary of results. You will examine how to understand their questions and perform exploratory data analysis to begin answering their questions. You will practice using your detailed data analysis to write a report then translate that data analysis for a presentation to a data science client. This course can serve as a template for working with a client from start to finish.
The following courses are required to be completed before taking this course:
- Exploring Data Sets With R
- Summarizing and Visualizing Data
- Measuring Relationships and Uncertainty
- Data Cleaning With the Tidyverse
- Classifying Data With Logistic Regression