That's a good point. How mutually exclusive is the optimization path for being highly employable versus self-employing or bootstrapping? Is it just a question of efficiency of time spent or is there more to it?
There are companies that you can't start via bootstrapping. I think a lot of expensive medical equipment design is in that class. I would also think that bio/nano tech is in that class.
I can program and have worked on software modules and have written my own utilities, but I still have a lot to learn conceptually and I still need to survey a wider range of technologies, especially related to databases and web development in the front and back end.
I have taken a semester worth of course on data bases and they didn't tell me anything useful about them. It was mostly impractical theory. The most disturbing thing was that the TA didn't know that a prepare statement in Java prevents you from SQL injections.
When it comes to databases the things you have to know are:
1) Try to never query the database directly in a way that allows for SQL injections.
2) Create indexes possible. It can make sense to experiment around with indexes to get optimal speed.
3) There something like transactions. In some settings a database automatically updates when you send it data, in other settings you have to commit or end the transaction.
Take a look at Nick Winters startup Skritter. He's doing a spaced repetition learning software for learning Japanese and Chinese Kanji. In contrast to Anki his software allows you to draw the Kanji. As far as cognitive enchancement goes I think learning Kanji is in the ballpark.
How much computer science knowledge does that need? Not that much. You need to know how to use a webframework like Django. You need to know javascript, probably something like JQuery, html, css. Some framework for iPhone/Android apps.
That's a bunch but you can learn as you go along. It also isn't deep computer science like machine learning and NLP.
In Nick Winter case it's interesting that he's a Asian studies minor. That's where he learned that the world needs a better way to learn Kanjis. That's where he felt the pain needed to focus on the idea. I feel similar to the biochemistry that I learned while studying bioinformatics.
If you want to produce medicial technology and are already able to program I don't think Biological Engineering is necessarily a bad choice. But I would recommend you to put the knowledge directly into practice.
An Arduino lilypad is cheap. Design the hardware with it and program it. Think about the kind of data you can measure and what to do with it.
I wrote this post up and circulated it among my rationalist friends. I've copied it verbatim. I figure the more rationally inclined people that can critique my plan the better.
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TL;DR:
* I'm going to commit to biomedical engineering for a very specific set of reasons related to career flexibility and intrinsic interest.
* I still want to have computer science and design arts skills, but biomedical engineering seems like a better university investment.
* I would like to have my cake and eat it too by doing biomedical engineering, while practicing computer science and design on the side.
* There are potential tradeoffs, weaknesses and assumptions in this decision that are relevant and possibly critical. This includes time management, ease of learning, development of problem solving solving abilities and working conditions.
I am posting this here because everyone is pretty clever and likes decisions. I am looking for feedback on my reasoning and the facts in my assumptions so that I can do what's best. This was me mostly thinking out loud, and given the timeframe I'm on I couldn't learn and apply any real formal method other than just thinking it through. So it's long, but I hope that everyone can benefit by me putting this here.
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So currently I'm weighing going into biomedical engineering as my major over a major in computer science, or the [human-computer interaction/media studies/gaming/ industrial design grab bag] major, at Simon Fraser University. Other than the fact that engineering biology is so damn cool, the relevant decision factors include reasons like:
The two implications here are that even if I am still interested in computer science, which I am, and although biomedical engineering is less upwind than programming and math, it makes more sense to blow a lot of money on a more specialized education to get domain knowledge while doing computer science on the side, than to spend money on an option whose potential cost is so low because of self study. This conjecture, and the assumptions therein, is critical to my strategy.
So the best option combination that I figure that I should take is this:
Tradeoffs exist, of course. These are a few that I can think of:
There is still the issue of assuring more-than-dilettante expertise in computer science and design stuff (see Expert Beginner syndrome: http://www.daedtech.com/how-developers-stop-learning-rise-of-the-expert-beginner). I am semi-confident in my ability to network myself into mentorships with members of faculty [at SFU] that are not my own, and if I'm not good at it now I still believe that it's possible. In addition, my dad has recently become a software consultant and is willing to apprentice me, giving a direct education about software engineering (although not necessarily a good one, at least it's somewhat real).
There are potential weaknesses in my analysis and strategy.
So for this "have cake and eat it to" plan to work there are a larger string of case exceptions in the biomedical option than the computing options, and definitely the media and design option. The reward would be that the larger amount of domain specific knowledge in a field that has held my curiosity for several years now, while hitting on. I would also be playing to one of SFU's comparative advantages: the quality of the biomedical faculty here is high relative to other institutions if the exceptions hold, and potentially the relative quality of the computer science and design faculties as well. (This could be an argument for switching institutions if those two skillsets are a "better fit". However, my intuition is that the cost for such is very high and probably wouldn't be worth it.)
Possible points of investigation:
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Thoughts, anyone?