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How to learn data science

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Re: How to learn data science

#11

Post by Lofkin »

pvnick wrote: post #3

Good article for beginners. A couple thoughts, just to build on what the author said: First off, data science == fancy name for data mining/analysis. Wanted to clear that up due to buzzwordy nature of "data science." Learn SQL - this is the big one. You must be proficient with SQL to be effective at data science. Whether it's running on an RDBMS or translating to map/reduce (Hive) or DAG (Spark), SQL is invaluable. I…

Great comment.

BTW, you can make interactive visualizations in pure python with bokeh: http://bokeh.pydata.org/en/latest/

Also with Blaze, you can use Pandas (or even Dplyr) syntax in python to query Hive, Spark and other large stores. http://blaze.pydata.org/en/latest/

Re: How to learn data science

#12

Post by mziel »

pvnick wrote: post #7
dummy7953 wrote: post #5

Earlier quoted context omitted.

You're basically describing stuff I was doing like 20 freaking years ago. Minus the Hive & Spark & Highcharts & d3.js - naturally. But back then I couldn't get any of my managers to understand or appreciate what I was doing. Fickle finger of fate.

Hell even William Gosset was doing "data science" when he popularized the Student T distribution while working for the Guinness Brewery back in 1908.

I lived through Statistics, Business Analysis, Decision Analytics, Data Analytics, Data Mining now Data Science. Same thing renamed over and over again.

Regarding post above, it's right. Data scientist is someone better at statistics (classical stats, bayesian, machine learning) than computer scientist, and better at programming (SQL, R/Python for building models) than academic statistician. Plus a teaspoon of visualization (ggplot or d3).

Re: How to learn data science

#13

Post by curiousjorge »

if I had some type of practical application that I knew could benefit from data science, like learning RoR to make a marketplace app for example, it would help a lot as I have a clear goal and route to achieve that. However, data science, machine learning, these are so broad, and seemingly complicated (my fear of complicated math formulas and statistics) and worse I don't know what I want to achieve out of it nor do I know what I want to make which really hinders the learning process for me. I need some incentive or reward at the end of the goal.

Re: How to learn data science

#14

Post by tyfon »

I've been working as an analyst for 7 years, it's only last couple of years I've heard of statistical analysis referred to as data science.

Am I missing something or is it just a new word?

Re: How to learn data science

#15

Post by curiousjorge »

minimaxir wrote: post #6

The actual problem with learning "data science" is making inferences and conclusions which do not violate the laws of statistics . I've seen many submissions to Hacker News and Reddit's /r/dataisbeautiful subreddit where the author goes "look, the analysis supports my conclusion and the R^2 is high, therefore this is a good analysis!" without addressing the assumptions required for those results. Of course, not every…

what you described is prevalent in social sciences. Ton of biases and causation/correlation error and putting blind trust in some arcane statistical analysis without knowing what they really mean. Conclusion: statistically significant is the magic word peppered throughout academic literature.

Re: How to learn data science

#16

Post by studentrob »

liviu- wrote: post #4
neovive wrote: post #2

"You need something that will motivate you to keep learning." This is so true and often forgotten. I am always learning new things, but the concepts that stick, beyond just the basics, are tied to specific projects or solutions to real problems. I'm typically ok with being a "jack-of-all-trades" for most technologies, just to stay aware of new things. However, when it comes to applying new concepts, skills, or tech t…

>"You need something that will motivate you to keep learning." This is so true and often forgotten. I'm surprised that both you and OP seem to think this advice is rare, as I've personally seen it mentioned more than a few times. Professors always brainstorm ways to motivate students, employers always seek methods to motivate employees, etc. The answer always seems to be something in the lines of 'do what you love' w…

> Professors always brainstorm ways to motivate students, employers always seek methods to motivate employees

Uhh.. You must have quite a fortunate streak of having great teachers and great employers. Speaking for myself, I had some great teachers, but finding a boss who seeks to motivate employees with the right challenges is rare. Bosses and companies generally assume your salary is the primary motivator.

Re: How to learn data science

#17

Post by achompas »

curiousjorge wrote: post #15
minimaxir wrote: post #6

The actual problem with learning "data science" is making inferences and conclusions which do not violate the laws of statistics . I've seen many submissions to Hacker News and Reddit's /r/dataisbeautiful subreddit where the author goes "look, the analysis supports my conclusion and the R^2 is high, therefore this is a good analysis!" without addressing the assumptions required for those results. Of course, not every…

what you described is prevalent in social sciences. Ton of biases and causation/correlation error and putting blind trust in some arcane statistical analysis without knowing what they really mean. Conclusion: statistically significant is the magic word peppered throughout academic literature.

Agreed. Fortunately, excellent social scientists really care about this -- see Andy Gelman's blog for many rants on this topic.

Re: How to learn data science

#18

Post by Balgair »

curiousjorge wrote: post #15
minimaxir wrote: post #6

The actual problem with learning "data science" is making inferences and conclusions which do not violate the laws of statistics . I've seen many submissions to Hacker News and Reddit's /r/dataisbeautiful subreddit where the author goes "look, the analysis supports my conclusion and the R^2 is high, therefore this is a good analysis!" without addressing the assumptions required for those results. Of course, not every…

what you described is prevalent in social sciences. Ton of biases and causation/correlation error and putting blind trust in some arcane statistical analysis without knowing what they really mean. Conclusion: statistically significant is the magic word peppered throughout academic literature.

I'll echo for biology and sports sciences (think moneyball).

http://www.wired.com/2009/09/fmrisalmon/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/

Re: How to learn data science

#19

Post by platz »

pvnick wrote: post #3

Good article for beginners. A couple thoughts, just to build on what the author said: First off, data science == fancy name for data mining/analysis. Wanted to clear that up due to buzzwordy nature of "data science." Learn SQL - this is the big one. You must be proficient with SQL to be effective at data science. Whether it's running on an RDBMS or translating to map/reduce (Hive) or DAG (Spark), SQL is invaluable. I…

Regarding SQL, have you noticed any increase in the usage of "window functions" (how important do you find them for your work?)

Re: How to learn data science

#20

Post by facepalm »

minimaxir wrote: post #6

The actual problem with learning "data science" is making inferences and conclusions which do not violate the laws of statistics . I've seen many submissions to Hacker News and Reddit's /r/dataisbeautiful subreddit where the author goes "look, the analysis supports my conclusion and the R^2 is high, therefore this is a good analysis!" without addressing the assumptions required for those results. Of course, not every…

I assume data science is often used in place of astrology. People just want to have something to cling to, to get over their fears and insecurity. So if you can generate some reassuring graphs, who cares if they are based on solid statistics or not?
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