Topics to cover for software developer interested in data analytics First of all I don't know if this is the appropriate place to post this question. If it's not, I apologize in advance. It seems like the most relevant Stack Exchange sub.

A little about myself:

I'm a software developer and have been working in the field for about 5 years. I have a two year degree from a community college that didn't involve much math above pre-calc high school level stuff. I've never taken a statistics course. 

Most of the software I write is business software. It's typically back end server or database stuff, never user facing. I do allot of data aggregation and normalization. 

Lately I've been thinking about expanding my skillset. Data and statistics have always interested and I'd like to learn ways to measure and interpret data. Ideally this would lead to thinking of useful metrics and uses for data that would help the company I work at.

The problem is I'm not sure what I should be looking into. There are so many data science topics and I don't know what would be useful for me to learn. I prefer structured learning environments such as courses or video series.

I know this isn't a great question... I'm just not sure where to ask and I'm not sure how to ask for what I'm looking for... or even sure what I am looking for. Any guidance or suggestions would be very much appreciated. Even if the suggestion is a better place to ask the question or a better question for me to ask. Thanks much.
Welcome to the community!! There can be a lot of answers to this question but I would suggest you the approach I took when I shifted from software development to the data science field.

1) Refresh your statistics and probability concepts. You should not go into too much details but you must understand basic things like Gaussian Distribution, Mean, Variance, Probability,etc.

2) Go through the basics of Machine Learning concepts. I prefer Andrew Ng's machine learning course on Coursera. That will help you build a strong foundation and will give you a great start in the field

3) Choose a particular language Python/R for building models. Though it's totally upto you but I prefer python as it has great libraries for machine learning as well as Deep learning.

4) Take part in competitions. We learn by doing not by taking only lectures. I suggest you should join Kaggle and the slack community out there namely, 'KaggleNoobs'. It's a great community. I learn everyday a new thing from there.

P.S: Data Science is a vast field. It demands from you various skill set like Data Analysis, Data Visualisation, Machine Learning,etc. So sometimes it can become frustrating too. But once you start enjoying it, you will become a master eventually.