Some of the things I’ve read lately:
- Creativity is Crucial in Data Science
- A couple different takes on data science careers:
- Two posts on what it takes to be a data scientist:
- How to think like a data scientist to become one: a summary of some of the basic skills needed, and some good advice for obtaining them with a focus on solving problems, and answering questions you’re most interested in.
- What makes a great data scientist? Insight into what will help you excel as a data scientist: focus on answering questions, knowing when a solution is sufficient, and being able to communicate effectively.
- Basic Project organization: One example of a standard project structure that could be used for data science projects.
- Exploratory Analysis of Federal STEM funding: A nice example, showing what a first data science project might look like.
- I’ve been working through a DataCamp course on data visualization, which reminded me of these discussions about the “Jet” colormap in Matlab:
- Only a genius can solve this tough puzzle: A nice guide to writing content that will be shared
- The Six Worst Ways to Brand Yourself: Good advice on what to avoid on your resume/LinkedIn profile.