Teaching Kotlin for Science

Does Kotlin suit modern scientific computing? How friendly is Kotlin for people coming from other languages, like Java, Python, or C++? How does an idiom-based approach to teaching Kotlin work?

Find out in this webinar by Alexander Nozik, scientific researcher and Deputy Head of the Nuclear Physics Methods Laboratory at MIPT. Alexander will share his experience of teaching a science-targeted Kotlin course for almost three years.

Categories: #Kotlin #MIPT #JetBrains

[harshitshukla]

On behalf of many enthusiastic programmer here in India, I would like to thank the Jetbrains team for the amount of efforts you guys put to arrange such talks. The channel is a great initiative.

[JolanRensen]

I think Plotly is quite nice, but the wrapper can be improved in my opinion.
The idea is that the wrapper is strongly typed, however oftentimes it accepts a Value, which can be anything.
You don't know, however, if what you give it will work or not, since it will compile just fine.
I understand, this is to enable similar notation to Python, but it's not clear when I need to give it a Double, Int, Color object, an rgb()-String etc.
Also, some parameters require just a Double, but other parameters require to convert my Double to a Value first.
And sometimes you need to type "value = something" and other times "fillcolor("")", instead of "fillColor = blabla"
It just looks inconsistent.

[johnpaulcarter]

Interesting. I used to deliver Java training (for Sun Microsystems), starting with the assumption of some experience of simple procedural programming and building the 5-day course around one core idea, which was obviously going to be classes/objects. Everything of interest could then hang off that. It worked very well and had good student feedback. I wonder if a similar approach could work for Kotlin - in which case, what could be the one core idea around which the other topics would hang? I’m thinking lambdas, but am still learning the language so am interested what others think.