Ra Inta has been working with us at Accelebrate for 6 months now and originally hails from New Zealand, but currently lives in Texas, USA. Ra teaches Python Programming at client sites and online. He's also a fantastic (and humorous!) writer and has authored many of our Python Blog posts.
We asked Ra to share more about his background, experience, and overall thoughts about the life of a Data Science trainer. Here's what we found.
For the entire video interview, please visit https://www.youtube.com/watch?v=XFxLqQ6NtIo&t=6s
Accelebrate: Tell us a little about yourself.
Ra: When I was four I wanted to be a fire engine driver and then my mom put me on a rocket ship five cent ride and then I wanted to be an astronaut - I thought that to be a scientist, you had to be an astronaut. I then discovered and fell in love with Albert Einstein and really wanted to be a scientist. I got my physics undergraduate degree followed by a PhD. In my PhD, I built guitars and looked at how the acoustics changed during construction. I then worked for a while on a project to harness the power of termites and being able to manipulate the way they communicate. I joined an exciting project called LIGO which looks at vibrations in space-time. In February 2016 we announced seeing the first two black holes colliding with each other which was really big news. The discovery ended up winning last year's Nobel Prize. It's been a really wild ride.
Accelebrate: What is the most exciting thing happening in the data science world these days?
Ra: Machine Learning is very exciting. I remember learning about neural networks back in the nineties and it was like, yeah, cool, but you need all this computing power… We are just never going have that much computing power in the near future. Then I blink then and it's here!
A really cool thing about data science is the community. Both the open-source software community and the data science communities are so embracing. There is something that reaffirms parts of humanity and helps to relate to others that are having the same problem as you are.
Accelebrate: How do you usually engage with the community? Is it mostly online or in-person?
Ra: You know, most of us are introverts so it's always kind of awkward. I talk with people through online forums and go to meetups, conferences and local events. It's like "hey", "do you like stuff"? You start by talking about the technologies you know and the tools you use in your day-to-day work.
Accelebrate: You mentioned R and Python. What are other tools or technologies are you using in your daily work?
Ra: R and Python are both so versatile themselves. To make the best use of them, I learn about and use related libraries. There is a project called Pandas within Python, as well as NumPy and others. I really like PyTorch for Machine Learning. I've been a recent convert to data.table with R. GGplot2 changed the way I think about how to do bots. I program in Bash a lot, because I like building with Raspberry pies. I use Linux a lot.
Accelebrate: What is your favorite language or languages?
Ra: I would have to say Python and R, for different reasons. I've been using Python for a lot longer than R. It really taught me a lot of new ways of thinking about data. It really did actually change my way of thinking and that's not a small thing!
Accelebrate: Do you have any tips or tricks for either Python or R Programmers?
Ra: My tips are a bit more general. With R, I recommend to people to just dive into the project. Take something you are passionate about and build something while learning about it. There's nothing like structuring how you do things through real, hands-on learning. Create a pet project focused on something you love. I have fun writing Instructable's, which are instructions about how to make things. I made this automatic kombucha brewing system just to regulate the temperature and things like that. Just sitting down and writing it out to someone who has not experienced it before can really help clarify things in your own mind.
Accelebrate: What are some of the most frequently asked questions in your data science courses?
Ra: There are questions like "what is a data scientist?", which hopefully we answered by the Courts. I also get asked what big data is. There are a lot of questions about probabilities and what a p-value is, or where something would be useful, which is always question that should be at the back of people's minds. Concepts don't attach themselves your brain very well if they are not relevant.
Accelebrate: How do you stay up to date on the ever-changing world of technology?
Ra: There are a couple of good mailing lists I subscribe to and a couple of online communities, like Data Science Central, which I quite like. I use Reddit a little bit, but not the data science subreddit, which is more for people asking questions like, how can I get into the field of data science? I do find Reddit quite interesting for the programming subreddits, and for keeping up to date with how frameworks are changing and how my old code is going to be broken by a change in something upstream..
Accelebrate: Are there any individual technical bloggers that you like to read or any podcasts or YouTube channels you enjoy?
Ra: I like Linear Digressions, Not so standard deviations, The Super Data Science Podcast.
Accelebrate: What's your favorite part about being a technical trainer?
Ra: I love seeing the light going on in someone's eyes. That is totally rewarding to see someone that really gets it. I'm sure that is the case with most instructors.
Accelebrate: Are there any big no-no's or anything to avoid when using programming languages like Python or R?
Ra: Don't spend all your time just taking a forum answer you find online without understanding what it means and how it works.
Accelebrate: Do you have any advice for children or teenagers who want to get either into technology in general or specifically into data science when they grow up?
Ra: We spend a lot of time emphasizing reading, writing, and arithmetic. I would more emphasis on people being numerically literate. People are constantly fooled by like really bad uses of statistics. I would like to see education where learning the language of numbers is just as important. This isn't really advice to kids themselves. It's really advice to what we as adults can hopefully do to change education for the future. Similar advice for kids would be just to play with their computers. You're probably not going to fry your computer by playing around with it. Get a Raspberry Pi and figure out how you make things. You can attach a temperature probe or a camera or something - have fun with it!
Accelebrate: What are your what are some of your hobbies outside of work? You mentioned music earlier; what kind of music do you like?
Ra: I still have one of my guitars from my PhD program. I still play it. I like playing around with raspberry pies as we talked about earlier.
Accelebrate: Thank you so much for your time, Ra. it's been really great talking with you and getting to know you. From everyone Accelebrate I want to tell you that we all enjoy working with you. We are looking forward to more fantastic data science trainings with you in the future!
Ra: Thank you! I really appreciate it.
Check out some of Ra's blog posts:
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