Thread by @mdancho84

I think the message in Data Science needs to be: Don't believe everything you read. 🧵

#stats #datascience

I'd like to thank Nico Cota for pointing me to this modified graphic from a recent Harvard Business Review article on "Prioritizing Which Data Skills Your Company Needs".

You hear Harvard Business Review, & you think this must be legit.

Well, in this case, they dropped the ball.

If you're coming up with an educational plan for your org in 2023, here are some tips:

1. Focus on #stats

This is the precursor to everything & will help you tremendously

2. Learn how to work with #Data

#DataCleaning and manipulation is 90% of what you will do

3. Build skills in #DataVisualization

This is a cornerstone of understanding, yet many #MachineLearning specialists can't do it

4. Skip over buzzwords until after you learn fundamentals (#AI, #DataScience, #MachineLearning)

You'll get to these after you learn #stats, data cleaning, data manipulation, & data vizualization

And if you are learning data science and feel as lost as I did when I first started, then I can help.

I put together a free 40-minute webinar that is value-packed with the 10 most important secrets that would have saved me countless hours.

Seriously. This webinar is insane. I packaged 5-years of struggling & finally figuring things out into a jammed packed 40-minute talk.

So tune in and I’ll see you in the webinar.

learn.business-science.io/free-rtrack-ma…