Reddit reviews Data Structures and Algorithms Made Easy: Data Structure and Algorithmic Puzzles

Well, the trick is to do one step at a time. Your goal is a very reasonable one, but you'll want to focus on the foundation first. For a non-programmer, I would recommend starting off with Code Academy or Coursera. The advantage of the second link is that it immediately provides you with a sense of direction while learning a language. Code Academy's Python tutorial is really nice in providing interaction with your code. Regardless, you'll want to first gain a sense of syntax on your language of choice.

After you're familiar with at least one language, the next most important thing is to become familiar with data structures and algorithms. This book on Amazon is amazing for giving beginner advice in the area: http://www.amazon.com/gp/product/1468108867

The book is not overly complex and mathematical compared to many other books, and it provides a fairly reasonable foundation for any beginner. If you ever want to practice writing basic algorithms out (optional), visit Codility's lessons to try things out. Once you can comfortably complete some of their lessons with a high grade and understand their topics, you should be ready to dive into the math/finance side. I feel that at this point, the Max Dama paper is a great way to get an overview of the basics. Regardless of the financial instruments you're trading (I've mainly worked with equities), you'll need a sense of portfolio management. Here's two books that may be worth running through:

http://www.amazon.com/Quantitative-Equity-Portfolio-Management-Construction/dp/0071459391

http://www.amazon.com/Expected-Returns-Investors-Harvesting-Rewards/dp/1119990726

They're both equities based (and I could be wrong here about FX), but it's probably a good idea to get a sense of how to measure returns. Regardless of the asset class you're planning to trade, all algorithms should be rigorously backtested and simulated (traded with virtual money) prior to being moved into production, and one of the best ways to improve your outcome is to know how to measure the returns and risks associated in your backtesting/simulations.

Hope this isn't too much information at once, but it should be a start. The first two courses throw-it-out mentioned in Coursera is a great start too.

Edit: I'd also take some time to browse some of the links on the sidebar in this subreddit. Some of those links are immensely helpful (especially the Statistical Learning one). Many of the strategy links are fairly easy reads and are recommended as well.

Just few resources to help develop problem solving/programming skills:

/r/dailyprogrammer

Project Eular

Data Structures and Algorithms (recommended a lot by Mosh Hamedani)

And the obvious /r/learnprogramming / StackOverflow etc. for when you need help.

I've been mostly finding that website coding is insanely helpful.

HackerRank, CodeForces, TopCoder are all great resources for "competition" problems (which translate really well into interview problems and problem-solving in general).

I read this book, it actually proved to be a lot more helpful for my Riot Games interview, since it had to do a lot with "in-depth" thinking, which this book is great at helping break down (I always found "Cracking the Coding Interview" to be way too high level, especially if you're in a pinch): http://www.amazon.com/Data-Structures-Algorithms-Made-Easy/dp/1468108867

(NOTE: If you're a primarily Java developer, there's an equivalent book for the above, just search "Data Structures and Algorithms in Java", from the same author)

I learned a lot more from that book than I did McDowell's, since I found that this author actually cared about doing "deep dives" into each of the topics presented. I own an earlier edition - not to say this one isn't great, I'm actually pretty sure the "algorithmic puzzles" he presents are a lot more relevant to current programming interviews.

There's also the age-old CLRS, which I found to be useful for any kind of theoretical computer science topic (Runtime analysis, big-O, etc): http://www.amazon.com/Introduction-Algorithms-Edition-Thomas-Cormen/dp/0262033844/

Let me know what you think! -- I've been using both of these to get my next job (hopefully full-time)! ^_^

Anything in this series is brilliant. Explains things at a very basic level, in friendly english. It will help you a lot. Good luck!