1–10 of 194 posts
What are some skills (technical or not) you think someone in my situation (or anyone else) should consider acquiring in 2019?
Ideally gain skills that will weather the potential recession that should start mid-year? Not sure what those will be exactly, but perhaps others have an idea...
Whether or not you need them today or not, whether you want to be in a leadership role soon or not, they are essential for anyone seeking to progress and you can’t start too soon.
There are many many ways to approach this and I’ll just offer two book titles that I believe would be beneficial.
1. Start with Why 2. Extreme Ownership
We need to think about the way we think and talk about the way we talk. I mean reflect on the state of things, instead of blindly increasing shareholder value. We glorify engagement, but we’re arguably glorifying how addictive our creations are.
What if apps maximized for less time spent, like help users just do their work and get on with living life?
When I work on web sites that deliver services I often picture users being in a hurry. People just want to get on with life, not live their lives within my server side rendered single page web app. :)
I've played with them in the past, but not spent enough time with them to be confident using them in production.
Leadership skills. Whether or not you need them today or not, whether you want to be in a leadership role soon or not, they are essential for anyone seeking to progress and you can’t start too soon. There are many many ways to approach this and I’ll just offer two book titles that I believe would be beneficial. 1. Start with Why 2. Extreme Ownership
https://www.youtube.com/watch?v=u4ZoJKF_VuA
Is the book worth reading, in addition? I see very mixed reviews.
I would recommend machine learning as a very useful skill to acquire.
I have to be more specific because "machine learning", "artificial intelligence", and "data science" are really large topics that can encompass difficult math and PhD research.
For application programmers, I think a very realistic subset is using an existing "machine learning toolkit or API" (e.g. Keras in Python) to analyze data and solve problems. You use the machine learning algorithms but don't necessarily write them from scratch. This level of proficiency only requires high-school math. The analogy would be knowing SQL even though one doesn't write b-tree algorithms from scratch or using the "=PMT()" function in MS Excel without deriving the annuity equation from first principles.
I think machine learning concepts (classification, clustering, etc) will become an expected baseline of programmer knowledge just like SQL was 25 years ago. Its usage will become more pervasive and will be utilized by more people that don't have "data scientist" in their job title.
Electronics is also kind of exciting right now in particular. The open hardware community while in it's infancy still, is growing rapidly. Notably, the ESP32 platform has allowed home brew IoT technology to grow very rapidly as it brings a processor and Wi-fi to a chip for less than $5.