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Here's the dirty little secret that people like you overlook - spending four years hacking around and hanging out on HN will teach you nothing about Big O notat

by elemeno 15y ago

Here's the dirty little secret that people like you overlook - spending four years hacking around and hanging out on HN will teach you nothing about Big O notation and how to analyse it or about advanced data structures. What it will teach you is plenty about chasing low hanging fruit and very little about tackling big and difficult problems. Sure, someone who's very driven will learn the same amount regardless - mostly by reading all the same books that someone who's gone to school will have read. But most people are not that driven. Most people are happy to hack around building webapps on the back of other people's libraries and then deluding themselves into thinking that gluing together a bunch of libraries and adding a pretty frontend counts as a significant achievement. Frankly, with your attitude you're doomed to hire the mediocre while the people with the brain and skills to do any form of non trivial analysis go elsewhere - as they well should.

randomdata 15y ago
This is not a binary issue. There are many facets to software development. Knowing Big O will not teach you how to best use git in a production setting. It turns out they are both useful and important. And that is the crux of the matter. A college graduate that is not driven to learn about the practical aspects of programming is no better for the job than the non-graduate who is not driven to learn about the theoretical side. After only four years of study, I would say that both applicants in the previous example are on equal ground. Both are lacking, just in different areas. It is not really clear at that stage which one of the two will have the drive to fill the gaps. The dirty little secret is that you cannot apply generic processes to find the best applicant. Doing so will lead to mediocre selection no matter which bias you choose.
- noahc 15y ago
  This is an awesome, insightful comment and really highlights what I'm getting at. You're right that they both have weaknesses. What I'm saying is I'm willing to go all in on the person who figured out much of it by himself using whatever he had available to him than the person who had a college instructor put together everything for him and then provide additional readings, power points, and web links to all their students. A smart person has to think their way out of a box. A resourceful person can just hack their way out of the box. I don't mind a little mess, so I'll take the resourceful person over the smart person everyday of the week.
  - randomdata 15y ago
    I'm inclined to agree. Since the differentiator is expected drive, one can reasonably conclude that autodidactic is more likely to have it. It is what got them this far. While many graduates also fit that description, it is difficult to filter them from those who graduated only due to social pressures and income dreams. For the theoretical programmers out there, you may recall that the future is independent of the past, given the present. I'm not certain it is worth hiring anyone based on their history. I would look to what they can offer today, and try to discern from that where they are headed in the future. It takes more effort this way, but you get what you give.
  - achompas 15y ago
    You're putting together a collection of false dichotomies in this thread. Let me muddle them up for you: CS departments are not all ivory towers. Consider the following opportunities in my department: (1) TA or grade production-quality software classes taught by Google engineers, with discussion on version control, code style, scalability, etc. (2) research and implement algorithms for diagnosing hospital patients more effectively using ML techniques, (3) push the frontier of computer vision in concert with former telecom engineers. Software development contains a large set of cool, non-trivial problems. Without formal CS training, you will not get to access those problems. This might change someday, but it is not close to true right now.
    - noahc 15y ago
      I really like number 1 and 2. Those both would be awesome examples of getting stuff done in a college setting. Thanks for pointing this out, as I've said earlier, I'm not sure we really disagree that much.
    - randomdata 15y ago
      > Without formal CS training, you will not get to access those problems. This is also a false dichotomy. You do not really know what people are working on outside of the college setting. Computer vision is pretty low hanging fruit for anyone to take on. I will grant you that it may be difficult to access medical data outside of the institution, but the same ML techniques can be applied to other data that is relevant. As a hobby farmer, I see all kinds of interesting places for ML on the farm. How many CS students are working with that kind of data?

by elemeno 15y ago

randomdata 15y ago

This is not a binary issue. There are many facets to software development. Knowing Big O will not teach you how to best use git in a production setting. It turns out they are both useful and important. And that is the crux of the matter. A college graduate that is not driven to learn about the practical aspects of programming is no better for the job than the non-graduate who is not driven to learn about the theoretical side. After only four years of study, I would say that both applicants in the previous example are on equal ground. Both are lacking, just in different areas. It is not really clear at that stage which one of the two will have the drive to fill the gaps. The dirty little secret is that you cannot apply generic processes to find the best applicant. Doing so will lead to mediocre selection no matter which bias you choose.

noahc 15y ago
This is an awesome, insightful comment and really highlights what I'm getting at. You're right that they both have weaknesses. What I'm saying is I'm willing to go all in on the person who figured out much of it by himself using whatever he had available to him than the person who had a college instructor put together everything for him and then provide additional readings, power points, and web links to all their students. A smart person has to think their way out of a box. A resourceful person can just hack their way out of the box. I don't mind a little mess, so I'll take the resourceful person over the smart person everyday of the week.
- randomdata 15y ago
  I'm inclined to agree. Since the differentiator is expected drive, one can reasonably conclude that autodidactic is more likely to have it. It is what got them this far. While many graduates also fit that description, it is difficult to filter them from those who graduated only due to social pressures and income dreams. For the theoretical programmers out there, you may recall that the future is independent of the past, given the present. I'm not certain it is worth hiring anyone based on their history. I would look to what they can offer today, and try to discern from that where they are headed in the future. It takes more effort this way, but you get what you give.
- achompas 15y ago
  You're putting together a collection of false dichotomies in this thread. Let me muddle them up for you: CS departments are not all ivory towers. Consider the following opportunities in my department: (1) TA or grade production-quality software classes taught by Google engineers, with discussion on version control, code style, scalability, etc. (2) research and implement algorithms for diagnosing hospital patients more effectively using ML techniques, (3) push the frontier of computer vision in concert with former telecom engineers. Software development contains a large set of cool, non-trivial problems. Without formal CS training, you will not get to access those problems. This might change someday, but it is not close to true right now.
  - noahc 15y ago
    I really like number 1 and 2. Those both would be awesome examples of getting stuff done in a college setting. Thanks for pointing this out, as I've said earlier, I'm not sure we really disagree that much.
  - randomdata 15y ago
    > Without formal CS training, you will not get to access those problems. This is also a false dichotomy. You do not really know what people are working on outside of the college setting. Computer vision is pretty low hanging fruit for anyone to take on. I will grant you that it may be difficult to access medical data outside of the institution, but the same ML techniques can be applied to other data that is relevant. As a hobby farmer, I see all kinds of interesting places for ML on the farm. How many CS students are working with that kind of data?