*Do you think Julia will replace python for this kind of analysis?
Have you seen the article “Parallel Supercomputing for Astronomy”? [Researchers use Julia on a NERSC supercomputer (650,000 cores) to speed astronomical image analysis 1,000x, catalog 188 million astronomical objects in 15 minutes and achieve peak performance of 1.5 petaflops per second]: Parallel Supercomputing for Astronomy - Julia Computing
On a broader basis, not only related to astrophysics, IMO, it seems to be still uncertain, however, possibly going into this direction, especially in the technical and data science field. The adoption is growing, however, in a sense, I would say that currently, the entry barriers are not at the same level as with Python. IMO, one important area that Julia is still very much behind is access to knowledge in particular disciplines. For example, if you want to learn reinforcement learning there are books on the subject with examples written in Python, if you want to learn about quantum computing there are books with examples in Python, if you want to learn … I do not know what … there are probably books on this subject with examples in Python. Even though, Julia is still a new language, I would welcome more decisive initiatives directly related to Julia in this area. (Disclaimer: I have a very limited knowledge about Julia initiatives in general.) On a positive side, please be informed that there are books, blog sites, conferences and packages that are second to none. It should also be noted that the community is a bunch of exceptional figures. I have not expected such a level of scientific knowledge in such a density.
*Do you think that switching to Julia would help the students that will look for a job?
I would say that Julia is a unique skill and growing. My understanding is that currently there are much more jobs related to Python and Python is very much supported in various fields. Python seems to look like a mature language with … various, specialized packages … coded in C. I would say that C / C++ coding is somehow regarded as a unique and a very valuable skill. I would not underestimate C and modern C++, especially if I be an astrophysicist. (Disclaimer: I am regarding astrophysicists as a very clever people). How will it look in 5 / 10 / 15 years from now? I think, that it’s still early to say. It should be noted that there were public releases with information about Series A funding at a level of USD 24m for Julia programming language parent. This implies potentially a very dynamic growth curve, however, at the same time a significant amount of risk. Usually, you are not risking this kind of money without a reason. Again, how it develops? More is to be said in about 3 years from now.
*Should we use Julia in the course?
I wish you a lot of fun coding.
I decided to post this edit as I found two interesting and extensive readings in the area of reinforcement learning that are available online and are directly related to Julia. They are not published books in a full sense. The first one I understand is scheduled to be published on paper in 2022 and the second is a material exclusively available online and is an add on to the already published book. When I was doing my research focused on published materials they were not showing on my screen. Hope it can be useful if by any chance somebody comes by this topic here.
ALGORITHMS FOR DECISION MAKING, MYKEL J. KOCHENDERFER, TIM A. WHEELER, AND KYLE H. WRAY [https://algorithmsbook.com/] - draft of a book that is scheduled to be published in 2022.
“Reinforcement Learning: An Introduction” by Richard S. Sutton and Andrew G. Barto; Second Edition, MIT Press, Cambridge, MA, 2018 [http://incompleteideas.net/book/the-book-2nd.html] and Julia code to generate figures from the book: [https://github.com/JuliaReinforcementLearning/ReinforcementLearningAnIntroduction.jl]