Category Archives: Career Development

Interview Preparation for Data Science Positions: Tips and Tricks

You can actually prepare for interviewing for data science positions by doing certain activities, like looking up common questions, and practicing answers.

Interview preparation for data science jobs can involve taking several simple, actionable steps to make yourself feel confident and ready to answer questions with ease. Read my blog post for my tips and tricks!

Researching Data Science Companies: How to Evaluate Your Future Employer

You should research companies offering data science job positions before scheduling an interview, because you do not want to be surprised during the hiring process.

Researching data science companies who might be your future employers, but you don’t know where to start? Read my blog post to learn my simple approach.

Answer Your Data Science Questions by Attending my Livestream Discussions on YouTube!

If you have questions about your journey toward a data science career, sometimes you can get them answered with online resources, but sometimes you do not get the information.

Answer your data science questions by attending my livestreams on YouTube and interacting in chat! Learn more about this in my blog post.

Paid Mentoring for Data Science: Is it Worth the Cost?

If you are wondering if you should set up a paid mentoring relationship with a data science mentor, you definitely want to read this. You want to make sure you get your money's worth.

Paid mentoring for data science can be worth the cost in certain circumstances – but not others. My blog post provides guidance on hiring a paid mentor.

Healthcare Data Science Newbie Do-it-Yourself Starter Kit

The tools for healthcare data science include both descriptive and inferential statistics

Monika posts her “data science newbie do-it-yourself starter kit”, with links to cheap or free learning resources for the data science newbie who wants to get started in healthcare analytics.

Two Takeaways from Danny Ma’s Machine Learning Panel: Understanding the Problem, and Understanding your Data

Roller coaster like an ETL pipeline that does automation

This lively panel discussed many topics around designing and implementing machine learning pipelines. Two main issues were identified. The first is that you really have to take some time to do exploratory research and define the problem. The second is that you need to also understand the business rules and context behind the data.

VP at Data Robot Tells Cautionary Tale of Data Science, AI, and Healthcare

Ice cream cone fallen upside down on a sidewalk.

I encourage those of you into data science and AI to sign up to receive digests from Data Science Central. I happened upon this web site when looking for some references for a book I am writing, and found some amazing articles. Since I’m into data science in and AI in healthcare, I was intrigued […]

Physical College Classrooms are so Yesterday. Why Are We Still Studying Deeper Learning in Face-to-Face Settings?

DethWench Professional Services - Never Stop Learning

My colleague who is a professor at Fitchburg State University studies deeper learning in face-to-face and online approaches in higher education. The idea is that if educators use deeper learning approaches, the students will learn more efficiently. Others have talked to me about deeper learning, and when I looked into it, I found that the […]

What is Open Access Publishing in Scientific Journals and Why Should I Pay for it?

Artistic rendering of conformational polymorphism of neurotoxic protein

I can easily tell you what open access publishing is – but then the first question you will ask is, “How did it get this way?” I will NOT be covering this belabored history of open access publishing in this blog post, but I encourage you to read this article in Nature to get a […]