It was starting my master's at university in electrical engineering.
For some reason, I decided to try to get a job as a software engineer to increase my income.
I knew how to program in Matlab & C. It was enough to pass exams but not enough to build a project from scratch.
I decided to learn the basics of Javascript, PHP, and Laravel.
I built a couple of small and simple projects (e.g. web page for my band with Laravel).
I searched for open positions in my town. I didn't meet more than 25% of the requirements for any of them.
I felt miserable but I applied to 10 of them.
I sent my CV (which was quite empty at that point) and a cover letter.
CV was the same for all applications.
I wrote a different cover letter for each position.
It took 3 days to receive the first invitation to the interview.
I went to the interview.
A guy asked me what do I now/show him.
I showed my projects and he liked them.
He asked me a bit about me and my master's studies.
I told him that I can work around 35 hours per week and still finish my exams.
He said they'll contact me if they decide for me.
After 5 days I received an email when can I start.
I must admit I was lucky.
Out of 10 applications I received 3 answers in total.
I also received 1 rejection (after 1 month) and another interview invitation (after 3 weeks).
After 1 year at the company, I asked the guy who interviewed me why did they go with me.
Answer:
* well-written email
* well-written cover letter
* done projects which I showed (although they were stupid and simple)
* confidence while talking
* honesty (knowledge, hours/week)
To sum up:
* build projects
* apply even if you don't know all the technologies
* put effort into CV and cover letter (different for each application; research company and their products)
* be honest
* be confident
• • •
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2️⃣ After I finished it I started playing around with Keras and scikit-learn to build a model of my guitar amplifier.
It took 72 hours of recording, 250+ hours of training, and 6 months of experimenting to conclude - ML algorithms like NN won't produce anything useful.
It reads and writes almost like the English language. You need a small amount of code to get a job done. You'll probably rewrite it at least 3 times.
2️⃣ 1st class citizen on cloud platforms
You don't want to deal with physical servers in a startup. You just want to run your app. Python has cloud SDK libraries, it runs on serverless platforms, it's used in ML services, a lot of examples in cloud docs are using Python.