Machine learning is the new electricity. There will be tons of positions available.
Ask HN: Is it a waste of time to teach yourself data science without a degree?
111–120 of 144 posts
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#112[deleted]
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#113I can't answer the question directly, but I will say this: machine learning is a lot of applied math. Suppose you are setting up a convolutional network to recognize some special object for a company. You will need to understand that math to know what parameters to tweak. Is it the learning rate? Is it the way you randomized the weights? Is it the activation function? Although, in fairness, I don't think even a PhD l…
Machine learning is only a small part of data science.
True.
However, I think what I said about Machine Learning is just as true -- perhaps even "more" true -- of Data Science.
Data Science is applied statistics. Knowing the underlying math is key to interpreting the results, knowing what to tweak and so forth.
(Wait, Hadley Wickham himself commented on my comment!)
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#114Earlier quoted context omitted.
I work for a technical statistical team in the financial world, we've been hiring PHDs lately to my team which has just meant exactly what this comment points out. I do a lot of the grunt work of getting the data sourced, cleaned and ready and am called the 'data wizard' and other such annoying names. What's frustrating is I can run the last lines of code and read and understand the output of the last step, but as th…
It sucks that you are doing the boring data cleansing job. And those people with degrees do the more interesting higher level analysis.
Data cleansing + pipelining requires a certain degree of cleverness.
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#115Learning something you like is never a waste of time.
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#116Most data scientists don’t have formal data science training. Most of the ones that go through our free fellowship (https://www.thedataincubator.com/fellowship.html - warning, I work at TDI) have STEM backgrounds and still land data science jobs at places like LinkedIn, EBay, Amazon, Capital One, Facebook, etc …
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#117A good programmer with even just a high level overview of ML and Stats concepts would be an incredibly valuable asset to a data science team. Most ML people are academics who tend to not have good software engineering skills, finding people who master both domains is really hard. Also to add to that most of the work in ML is feature engineering, data cleaning, testing and building pipelines which all require a good s…
I'm currently working through Andrew Ng's ML course on Coursera. It's definitely high-level (though a fantastic overview of the fundamentals), and I plan to take something a little more mathematically rigorous at some point, but I'll probably want to take some refresher courses in Linear Algebra and calc before doing so. I'm not trying to learn about ML for purposes of employment, It's somewhat relevant to my current…
> I'm currently working through Andrew Ng's ML course on Coursera. It's definitely high-level
I agree that it is "high level" and glosses over (purposefully) the nitty-gritty details of the "black boxes" for the most part. I say this as someone who took the first incarnation of the course, which was known as "ML Class" in the fall of 2011, before Coursera came about.
Despite it being high-level, though - this is what one of my "classmates" was able to create, about halfway or so thru the course:
http://blog.davidsingleton.org/nnrccar/
In 2012, I completed Udacity's CS373 course (https://www.udacity.com/course/artificial-intelligence-for-r...).
Today, I'm currently in the second term of Udacity's Self-Driving Car Engineer Nanodegree (the current lesson I'm on actually is a part of CS373 - so it's a kind of review lesson for me - heh). I'm having a great time learning about more in-depth understanding and knowledge relating to self-driving vehicles. Much of the learning can be applied to other areas of ML as well (learning how to use and abuse TensorFlow and Keras, for instance).
> A big shift in career, from software engineer to 'data scientist (or whatever they call it)' is probably not possible at my advanced age (37).
Don't let that stop ya! My plan after finishing this Udacity course is to actually work toward getting my BS and maybe MS in Comp Sci. By that time, I'll be well into my 44th year of age. I don't know if any of this will lead to a different direction in my career, but that isn't something I am really worried or planning about. I'm currently happy with where my career is; it pays the bills and allows for some fun, too. But if it should lead in another direction, so be it! I figure having this knowledge can't hurt me as a employment candidate, and will likely be seen as a plus. Worst case scenario, it will make my hobbyist robotics projects more interesting.
I figure I have another 20 or more years in me doing software development (assuming it remains a career option, of course); I personally have met more that a few other developers that age or older who are still making a living at it. So I'm not ruling out the possibility of a lateral move toward something involving my knowledge of machine learning.
Good luck with your studies!
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#118Just think about how much better you need to be than someone with actual credentials (e.g. PhD in machine learning and real presentable experience) and then assess whether you are good enough to compete with them.
If you don't know how good you are relative to the competition with PhDs, then it would be worth it to have a discussion with people who have a taste for the field.
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#119Earlier quoted context omitted.
For data science specifically? Remember, this question isn't about general CS.
The original comment sounded like general advice not specific to data science. I was thinking about it in the context of general CS/programming. But even in data science specifically, in my experience the focus in hiring is towards actual skills and less towards credentials/qualifications. I recently (few weeks ago) interviewed with a data science company for a data science role as someone with a software engineering…
Data science is absolutely based on degree level. Software engineering, maybe 50% of people care about your degree.
Re: Ask HN: Is it a waste of time to teach yourself data science without a degree?
#120Don't have a degree myself and about a third of the people I hire also don't have one. Why? Because I don't give anything about them. I'd say if you don't want to work for a large, respected company first , it's a waste of time. Your degree is your entry ticket to your first job, not more. Later on, you can even work at Google if you want - just make a great product and get acquihired. Three tips on what you should d…
> I'd say if you don't want to work for a large, respected company first, it's a waste of time.
I wouldn't necessarily say that.
I don't have a degree (well, an Associates that ain't worth much). I've been employed as a software developer for 25+ years now (since I was 18 years old).
I wish I had pursued a degree, though.
Back then, when it came to my education, I was pretty lazy - at least when it came to more structured learning. I liked to pursue stuff on my own, though, at my own pace. I've done well in that manner.
In 2011, I "discovered" the idea of a MOOC: I took Andrew Ng's "ML Class" - and successfully completed it. That led me Udacity's CS373 course in 2012 - which I also completed successfully.
That isn't to say I didn't struggle with both of those: I had no experience with probabilities and stats, and I hadn't touched linear algebra since high school. But with the help of resources on the internet and elsewhere (along with help from others on the internet, and fellow classmates), I managed to complete both successfully, and I learned a lot in the process.
Last year, I started Udacity's Self-Driving Car Engineer Nanodegree. Today, I'm working on term 2. We're dealing with localization - basically learning SLAM, which was covered in the CS373 course, too. Prior to that, we learned about how Kalman filters (standard, EKF, and UKF) all worked to integrate sensor data. In the first term, as part of one of the projects I implemented NVidia's End-to-End CNN to drive a virtual car around a track.
All of these experiences, and others outside of all this, have taught me that perhaps I cut myself short by not pursuing a degree when I was younger. My current plan is once I finish this Udacity course, I'm going to get my BS online, then work toward an MS in comp sci. It isn't a matter of "I think I can do it" - I know I can do it. It's more a matter of absoluting proving it, and likely learning a lot more along the way.
I don't think a degree is a waste of time, unless you intend never learning more stuff as you "grow older". If your only goal is to "make money" and all that, maybe it is. To me, though, had I gotten my degree back then, I believe I would be much, much further along today. I can't change that, though - so all I can do is move forward.