Edit: Great responses, I learned a lot, thanks!
I had expected that it was not economically viable for agriculture, but the article has one source claiming it is actually quite affordable, given current water prices in the west.
A large portion of the article tries to give both sides a voice.
To make a Minecraft analogy that more people might understand, is it closer to redstone or command blocks?
There are three types of combinators: arithmetic, decider, and constant.
Signals have a channel name (one for each item type and a few dozen other options) and an integer value.
Arithmetic combinators can perform arithmetic operations on one or all signals with one signal and a constant integer, or two signals.
Decider combinators perform comparison operations.
Constant combinators emit constant signals on a given channel.
There are also abilities to detect state on some other items and cause behavior to change, the equivalent of observers, dispensers, pistons, etc.
Overall, I'm also happy with the course. I was expecting a little more degree of difficulty and a little higher workload than what I've run into so far. If you're an experienced developer with a Github account, the first course can be completed in a couple of hours. The R Programming course was more along the lines of what I was expecting. So far, the third class is closer to the first than the second (in terms of difficulty...does require a bit more time).
Going into the course, I wasn't expecting to come out a "data scientist" ready to land a full-time job in the field. My experience so far confirms that expectation. But it's a fun course, a good way to get started in R, and a good way to spring-board your exploration into the field. It's nice to have deadlines as a motivation to keep on track and stay on a track for learning. I'm hoping by the end of the curriculum I feel confident enough to try and land some small free-lance projects.
I'm paying for the "official" certification. I'm not sure if it's really worth it, but at $50/class it's not putting a big dent in my finances.
Now I'm taking the next three. They are a good continuation that picks up where the first three left off. I was looking forward to the Statstical Inference class. It has been almost 10 years since I took intro to stats in college. For someone without any stats background this course will really step up the difficulty. I was even more disappointed with the lectures on the stats cours. The yellow highlighting as he reads each line on the slide is extremely distracting. But the content is exactly what I was hoping for.
I've done a little hacking with R for data heavy analysis at work when excel couldn't handle the data. I'm really glad to be taking advantage of this opportunity to get more experience with it in these course. My day job is implementing the 'production' side of this kind of data processing with java and hadoop in the healthcare space. Hopefully this specialization will help me better communicate with our clinical/science teams.
Also, don't forget that you can use @Resource (jsr250), not only @Autowired.
The author also says:
> So reuse and decoupling are opposing forces. I find myself siding with decoupling.
The developer has to make a balance between reuse and decoupling. In my opinion everything doesn't have to be 100% reused or decoupled.
But I don't like using auto wired in the main code because it means I am required to use that wiring for every use. I find that we want to use classes in a few different ways, and keeping the dependency definitions and configuration values in the XML decouples it from the code and increases both reusability as well as exposing the XML configurations after deployment so that a recompile isn't required in the field.