Episode 47: (Data Bites) Applying an Academic Approach to Learning Data Science at Work

Today’s Data Bites is all about how we can transition what we learned about the possible improvements for Data Science graduate programs into programs to increase the skills of your employees.

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Music for the show: Foolish Game / God Don’t Work On Commission by spinmeister (c) copyright 2014 Licensed under a Creative Commons Attribution (3.0) license. http://dig.ccmixter.org/files/spinmeister/46822 Ft: Snowflake

Transcripts:

Welcome to data tour the podcast about data culture at work at home. And on the go. I’m your host, Jordan Bohall. To stay up to date with everything data controller, be sure to like and subscribe down below. Furthermore, be sure to follow us around the internet at data to her pod on Twitter, at data couture podcast on Instagram, and at data couture pod on Facebook. Of course, if you’d like to help keep the show going, then consider becoming a patron at patreon. com forward slash data couture. Now, no under the show,
system.
Welcome to data tour. I’m your host Jordan on today’s data bytes, we’re going to be talking about how the last two episodes namely education, the the graduate programs in data science, how they have some areas for improvement, they have some gaps that need to be overcome. We’re going to be talking today instead about how this new approach to a data science education. And Emily one that’s interdisciplinary, can be applied to upscaling employees at any organization. So for the very last time, I promise for this particular campaign. Please remember that I’ve got a Kickstarter going and you can help support at dedicate tour.org forward slash Kickstarter, who last time you guys have to hear me say that. In any case, let’s get on to the show.
You might be asking yourself, Jordan, how can I apply an interdisciplinary approach to learning data science in my organization, my organization is a university. So how do I do this? Well, let me give you an example of how I’m approaching it at my own organization. And I think I’ve said this before, but I am currently starting with what I’m calling my shadow analytics group, my shadow recruits. And what we’re doing is teaching them how to use our visualization and automation tool Power BI. We’re teaching them how to do analysis within this tool set as well as how to connect up and see the data that we have built in our data warehouse, how to request data, how to
find data in their source systems, their particular experts in so that they may have the correct data for the analyses that they are being recorded vested. So you know, this is a fine first step. In my opinion, it’s kind of jumping the gun. But to be frank, because of resource constraints, I need more people who have skill sets within Power BI itself, instead. And I recommend this method to more than just jumping the gun and getting a shadow analytics team. But you know, do what you have to do. any case, starting in January, we will have been all moved into our brand new corporate building, which let me tell you all is extraordinarily gorgeous. And I for 1am, very excited to be moving into the space. But nevertheless, in this new corporate building, we have dedicated space just for learning and development we have effectively, a room with risers, or it’s kind of like stadium seating, and a lectern and lots of technology. And so in this room, I will be leading a are University style course and which I’ll be teaching what I’ve taught to so many students in the past and so many times, namely, an introduction to critical thinking. And I’m not talking super complex logical reasoning, mathematical reasoning, philosophical reasoning, any of that kind of thing. I’m talking about your bare bones, critical thinking skills, if a then B kind of stuff, right. And so I’m going to start with that. But then build up into more complex reasoning tasks. And hopefully, as this trial program, this test, education system or platform continues to progress, we’ll be able to inject things like creative thinking and critical problem solving and creative problem solving. And then once we get past that stuff, well, then we’ll start going into some more of the statistics and some of the linear algebra and some of the coding and some more of the Power BI and visualization techniques, right. And then, of course, if there are any people left, at that point who want to continue taking my course, courses, I suppose, then we’ll get into more of the the data science fundamentals and some of those things. And so the idea is identify somebody at your workplace who has taught these kinds of things and just start, you know, drum up some interest, it doesn’t have to be everybody all at once. But as you continue as weeks and weeks go by, and to be very clear, I’m running this just like I do any other university class, I’m doing a 16 week, once a week sort of class, where we go through the fundamentals in the background on the history, the theory for all these different areas. And my hope is by having this kind of groundswell, this grassroots this guerilla style education platform. One, I won’t be too off putting because people don’t have to spend time outside of work to go to a university, because you know, everybody has lives and kids, they can get the necessary training in house. And my hope is that, by doing it this way, by presenting a lot of different topics, just like I would like to do in the graduate program in which I teach will have well rounded team members and employees who are well prepared to be data literate citizens for this century. And by proxy, my organization will benefit greatly because it too will have this growing number of people who can do all these different skill sets and can connect all these different dots and be able to perform and understand data, utilize data and gain insights, and then act upon data and the data products that are then produced. So that we can help our membership out, which is our driving force. We care about the financial health of our members. But also make sure that my organization sticks it out stays around for the long term. If you guys have different ideas about approaches to work again, leave a comment down below. If not have a good three day weekend. At least if you’re in the US. I know I have some listeners in Munich and parts of England and Australia and all sorts of places but nevertheless in the US. Have a good three day weekend, and I’ll talk to you next time. That’s it for the show. Thank you for listening. And if you liked what you’ve heard, think consider leaving a comment or like down below. Stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod. consider becoming a patron@patreon.com forward slash data couture music for the podcast. It’s called foolish game. God don’t work on commission by the artist spin Meister used under the Creative Commons Attribution 3.0 license,
writing, editing and production of the podcast is by your host Jordan Bohall.

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