Getting programming job roadmap? (post-theory stage)

People who already got jobs after self-learning, your advice will be “gold” for me here!

Hi everyone,

I am overwhelmed about the whole issue of self-learning Deep Learning,
I’ve just finished my first degree in Plant Sciences and want to be a programmer in the neuroscience field (esp. Brain-Computer interface).
From my experience Deep Learning is implied a lot in the comp. neuroscience field, plus there a lot of job opportunities in other fields like autonomous driving and medicine, so from that, I decided after month of studying the fundamentals of neuroscience , to study Andrew’s Deep Learning specialization.
It has been more than a month since I started, and it goes pretty well (and slow) but I can finish it in two months from now.
My biggest concern is how long is it going to take me to get a job after finishing this specialization.
How long should I work on my own portfolio? a month? 3 months? much more?
Plus there are a lot of people saying that you should know calculus and statistics and it’s super confusing, because of its non-specificity.
I know that in start-ups there are lower demands and thus they are an effective way to get the foot in the door,
but I am really confused and worried about my vague future, does anybody has some thoughts about what I’ve just written?
Can anyone just mention his own experience and how long did it take him to build portfolio right after finishing learning the basic theory?

Thank you very much,

So the tricky thing that I think you’re going to end up facing is that you’re looking to get into a rather specific field, and therefor a smaller and more competitive job market. Just finding jobs in your area of interest is going to take some work and creativity.

The importance of a portfolio is inversely proportional to the formal training and qualifications on your resume. Ask yourself “Am I showing something that competes with someone who has a CS degree and Machine Learning coursework?”

Math does often come into play with a lot of programming jobs, and I would assume that deep learning especially may rely on a a fair amount of applied statistics (and maybe linear algebra or differential equations?) I wouldn’t fixate on this too much, but if you have the time you might want to watch lectures from a free MOOC on these subjects so that you can at least be familiar with what it is. — I’ve never applied for jobs in machine learning, but I have been asked about linear algebra in a few interviews. Nothing super in-depth, but they did want to know my math background.

Thanks! You answer about the linear algebra made it more clear!
I want to make it more clear - comp. neuroscience is more like a dream job, and thus I am ready to work from time to time in other jobs that are still connected to deep learning,
thus I am not going to rush into one very specific market and will always keep other options open,

Still my main question is about the time it takes to get really ready for a job after learning the theory.
Could you tell about your expirience how long did it take you to gain the basic expirience / portfolio to get a job after learning the theory or the basics?

Well, I don’t work in machine learning, so I can’t speak to that. I also took a more traditional path, with a BS in computer science so it took me 4 years :slightly_smiling_face:.