Every company needs a data employee of some kind. Some of your favorite companies need entire swarms of them. When Netflix recommends a category of programming to you called “Irreverent Rant Stand-up Comedy” or "Hidden Gem Fight-the-System Movies” it’s because they have enough data to have created 76,897 different micro genres and they want to recommend the perfect show for you to watch next. That’s just the tip of the iceberg for Netflix data, in 2006 they announced a contest to improve the accuracy of their predictions with a prize of 1 Million dollars to any team that could write the winning algorithm. The winning team was made of statisticians, machine-learning experts, and computer engineers who worked tirelessly for 3 straight years on a huge data set of over 100 million movie ratings.
And if you need more convincing, these jobs are both the highest in demand and the best paying for 2016. Check out these sweet salaries.
The following is your master list to become a Master of Data this summer.
Python: If you know one programming language, you know them all, don't let Python inexperience hold you back. Brush up on your Python or see it for the first time at Code Academy. You can knock that one out in a day. It's free and not that hard. If you've ever changed the color of a blog title you already have the basics of programming down.
SQL: People make this out to be a big deal but it's just you typing a word like "CREATE" or "INSERT" into a database and then it does what you want it to. Administrative Assistants use SQL to find out if you registered for your fall classes in college. Do you have 3 hours to completely smash SQL? Go back to Code Academy and knock it out.
Statistics: As stated earlier this can be long and painful or extremely interesting. There are free courses online from MIT and Berkeley, video tutorials on youtube, and you can even stream a course through your media player such as a roku on your tv. I had to spend 3 months analyzing cereal so I'll let you find your own, better stats course.
Good luck Data Scientists, feel free to reach out if you have any comments.