The interest thing on your list is that neither Nick Winter, Cal Newport or Scott Young have jobs at some company. If you take those people as your role model, are you sure you want to focus on the goal of getting a job?
I might be a bit biased but I think it easier to do a startup when you can do computer programming.
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?
How much computer science knowledge is necessary for startups, do you think? 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. That’s even excluding some of the trendier hotspots like semantic web, NLP and machine learning.
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.
The interest thing on your list is that neither Nick Winter, Cal Newport or Scott Young have jobs at some company. If you take those people as your role model, are you sure you want to focus on the goal of getting a job?
I might be a bit biased but I think it easier to do a startup when you can do computer programming.
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?
How much computer science knowledge is necessary for startups, do you think? 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. That’s even excluding some of the trendier hotspots like semantic web, NLP and machine learning.
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 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.