Found 6 comments on HN
cdl · 2018-01-15 · Original thread
The first chapter of "Data Smart" ( gets into some more advanced but practical tasks in Excel. The material is accessible to the beginner and assumes little prior knowledge of Excel.
strictnein · 2016-11-08 · Original thread
Can't answer whether to learn R or Julia, but for a more general education on Data Science, this book might be a really good fit for you:

Data Smart: Using Data Science to Transform Information into Insight

All the work is done in Excel. I enjoyed the book quite a bit. Author is Chief Data Scientist for MailChimp.

You can use Excel for more than many people think. For some great examples, and with only a single chapter at the end devoted to R, see Data Smart, by MailChimp's Chief Data Scientist:

EvanMiller · 2014-02-08 · Original thread
If you want to learn the nitty-gritty of machine learning and optimization, I highly recommend his book, Data Smart:

It's one of the few books on the subject that doesn't get bogged down with mathematical notation, nor does it cheat with "And Then A Miracle Happens" library calls. The book is primarily aimed at business analysts, but programmers can get a lot out of it too.

I agree that the notation is tough. Especially for folks who need to learn to do this stuff as a one-off and not as a career. That's why I wrote a book that teaches the algorithms with nearly no math notation while trying to be very rigorous:
Yeah, google drive spreadsheets are only good for sharing fairly static small sheets. I just wrote an intro data science book that uses spreadsheets to demonstrate certain algorithms (simplex, kmeans, modularity, LOF, etc.) And in the book I warn the reader to not use Drive. Slow, clunky, and the Solver implementation is garbage. Plug:

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