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What does it take to become a good data professional? The answer is obvious: become an autodidact!
Given that the industry constantly changes, the only way to stay relevant is constantly learn. By improving your knowledge and skillset, you can guarantee that you won’t be automated out of a job!
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Welcome to data couture, the podcast about data culture at work at home. And on the go. I’m your host Jordan bohall. If you like what you hear, be sure to subscribe lows, get the latest episodes wherever you get podcasts. And if you’d like to stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod. Finally, if you’d like to help support this in future episodes,
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Welcome to data couture. I’m your host Jordan and on today’s episode, we’re going to be talking about the importance of being an autodidact. You know, the last few episodes have been somewhat dreary or scary, right? We’ve been talking about the artificial intelligence, fear paradox and the death of critical thinking and work in our everyday lives. But today, we’re going to turn to something that’s far closer to my own heart, namely, self led learning. Stay tuned.
So what is an autodidact? Well, simply put, an autodidact is someone who’s simply self taught. You might be wondering how is this related to data or data culture, data driven cultural transformations, or machine learning or predictive analytics or business intelligence or the data professions generally? Well, in case you didn’t know this already, the field is rapidly changing. So even if you exit the University with a PhD in computer science, or statistics or mathematics, or in my case, the philosophy of mathematics, the field is going to be very different from when you exited your program and a year, six months, the fields constantly changing.
And so being an autodidact is related to the data profession, because you must be continually learning you must be able to teach yourself, the new techniques, the new languages, the new methods, the new visualizations, the new ways of presenting the data so that multiple people, your customers understand exactly what’s going on. So, again, what’s an autodidact? It’s a self taught person. What does it mean to be an autodidact? It means that again, regardless your particular education level, you’re willing and you’re able to teach yourself the various skills that you need to survive in your life.
By survive, I mean, pick up those skills that allow you to grow your career and succeed in overtime. Now, we’re going to talk about this in the second section about how this actually appears and our everyday and working lives. But in my opinion, you don’t necessarily need to go to university, you don’t need another graduate degree, you don’t need a masters or multiple masters or a PhD, to be an autodidact. You don’t need any of these degrees to be successful in the data profession. Of course, many people go to university in order to learn how to learn. I’m no exception. That’s arguably what a PhD in philosophy does. It’s what it teaches you among, of course, various other talents. But if you are able to be rather rigorous and your own reflection, your own consistent education through YouTube videos, or through reading books, or going through online courses, or simply learning by doing and making mistakes and searching Google, like, basically every other person does, even in the professional industry, to be a good coder, as the saying goes is to be extraordinarily good at googling, and most autodidacts are.
So in this episode, we care very much about this perhaps fundamental skill set to what it means to be a good data scientist or what it means to be a good data professional. That is the very resolute and audacious means and audacious, audacious perspective, audacious character, that’s what I want to say, to learn something new to learn something that is beyond what you currently know. That’s what makes a true data scientist, in my opinion. So let’s move on to the second act, where we see how this plays out in real life.
So you’re probably thinking to yourself, but at least some of you are thinking to yourself, great Jordan now you’re saying that I’m top of all the statistics, and all the coding and all the visualization work and aesthetics, understanding, and all the business knowledge, and just all of the basic fundamentals of what it means to be a data scientist aren’t enough. Yeah, that’s what I’m saying to you. I’m saying that without this deep drive to teach yourself new skills and new talents, constantly, you probably won’t be at least you won’t be a successful data scientist, you might be a data scientist, but you’ll quickly lose out to people who are very capable at teaching themselves new skills and new talents. So what do I mean by an autodidact?
There are lots of examples throughout history. But here’s some examples from my everyday life. I have a team of engineers and DBS and people who are transitioning into the data science area. But more specifically, I have particular team member, a particular employee who comes from a very different field than data science and this person. Well, very good, say, and finance and accounting
came to my team without the underlying skills of the coding and the stats and the visualization understanding, right?
However, this person, they’re very motivated, let’s put it that way, they’re very motivated to learn, and they’re very motivated to enter this field. And so, of course, let me back up to be an autodidact. You don’t necessarily have to do it alone, you don’t have to do it on your own right, you can rely on your network. And in this case, this employee of mine has expressed their interest to the group. And they’ve expressed that they deeply want to be a data scientist, great. My team can rally around them, they are regularly teaching this person, various skill sets and visualization and how to use the tools for automated dashboarding, for example, he’s been given books, about stats about the various programming languages.
And I have no doubt in my mind that this person is going to take these and run with it. And I’ve told this person, embarrassingly in front of the rest of the group that once they have all the normal technical skill sets of a data scientist plus all of these financial and accounting skills, they’re going to be a kind of unicorn in our field, they’re going to be a kind of unicorn, and data science because not only can they do the technical stuff, but they can put their money where their mouth is they can do the important things of running a business, the finance and accounting pieces, right?
That’s one example in my life. Another example is practice. One of my best friends again, trying to enter this field. Granted, this person he is about to graduate, I think, with his PhD, but nevertheless, he’s very, very close. Right? And so you’re thinking, Oh, he’s got a PhD that has meaning is that autodidact? Well, he’s an autodidact, because he had no background in data science. Granted, he is rather talented mathematician, rather talented, critical thinker. However, he took it upon himself to learn all the technical pieces, he’s becoming more and more proficient in the business side of the house. He just landed a job, which I’m very happy and excited for him about as what do they call him a junior analyst, maybe something like this, but nevertheless, he’ll be doing a lot of data science projects and his job. And he did it all just because he was interested because he had the grit to be able to pick up this new skill set, john into the unknown, and just roll with it.
Right. That’s what I mean by an autodidact. Okay, let’s talk about two more examples of autodidacts in my life. And these two are rather personal to me. I guess the first two were two but even more personal. The first one is my mom. She is nearing retirement or kind of retired. Anyways, she is at that stage where she’s ready to do away with her chosen career and try something new. And she has an what I consider an excellent idea she wants to become an influencer. Now, I know that most of you are going to roll your eyes at that. Because influencers are 20 somethings or early 30 somethings who are very good at social media marketing, I suppose. Or maybe they’re just like, really gorgeous people, or maybe they’re famous music or whatever they are.
However, there’s a whole segment of influencers that just talk about lifestyles, talk about what people like them are going through. Okay, so my mom, I think she has a very, very nice niche audience. niche niche niche, in any case, a very nice audience that is probably rather underrepresented, namely, people from the Midwest, specifically women from the Midwest and that retirement age, who have lots of great interest, lots of complicated and varied interests. And so what does my mom do? Well, she’s an autodidact. Of course, she researches everything she can she reads about all the various methods through which these so called influencers are making waves. And she’s just going for it. Of course, she wants to do it with me. And I’m not an influencer by any means.
But nevertheless, it’s a nice process. She’s learning on her own to do something completely foreign to her because she can, she’s interested and she’s got the determination to do it. And that’s awesome. And now, the fourth example, the last example is my wife. So my wife, I haven’t spoken about her yet about on the podcast, but she is a classically trained dancer, she does and she’s gonna kill me for this, forget it wrong. She’s a contemporary dancer. And in my opinion, does quite a bit of avant garde work. She does contact improv, she does a few other styles of dance. She’s definitely gonna kill me. Nevertheless, she has gone through her school, she started when she was in her teens. She finished up with the masters and MFA in dance.
But now she’s trying something new. She’s trying massage therapy. And now there’s quite a bit of contention if you’re on the artistic the the dance world, whether or not it’s legitimate to do massage therapy now that you’re a dancer, but it’s there’s a clear through line there and the sort of body work in the sort of movement and the sort of things that dancers go through and massage therapist go through. And so she put it upon herself to go to this top notch school out in Colorado, far away from home far away from her family and learn how to be a massage therapists.
Now you’re saying, Oh, she’s going to school, that means she’s not an autodidact? Well, I beg to differ. Lots of people go through the school. But none of them are nearly as talented and as good at this particular thing as good at this particular skill is my wife. And it’s because she has this ability to pick it up to learn to just strive to be the best she can be in massage therapy. And she does that by constantly thinking about that, which is a serious and perhaps underappreciated trait of being an autodidact because of that she’s getting job offers left and right from all sorts of people in her new field.
And that’s amazing. So, now let’s talk about how you too can become an autodidact.
Now, in the previous segment, I spoke about certain aspects of, of those examples of people who are autodidacts, there was grit, there was consistency, there was fearlessness, there was perhaps acceptance or visualization of the future that you want to be. And there was also a reaction to a kind of fear. So let’s talk about each one of these in turn. What does it mean, to be an autodidact because you have grits? Well, it means that you’re going to come across quite a few things and your self learning and your self teaching that you might not be able to figure out. However, you’re probably not the first person to come across this particular problem in yourself learning to have grit as an autodidact just means that you can overcome that challenge, it means that you’re not going to stop just because you face this particular wall, or you have to climb this particular mountain, to get to that next stage where you feel more and more confident in your particular skill set or newfound knowledge about consistency.
Well, you can’t simply every once in a while and try to learn something and expect that it’s going to stick. In order to truly teach yourself you’re going to have to be consistent with you’re gonna have to do it, you’re going to have to try to learn or attempt to achieve this new skill, this new bit of knowledge over time, and you’re going to have to do it every single day or every other day, you know, you’re going to have to be in a regular schedule, to be able to do that. The next part is a kind of fearlessness, you’re jumping into the unknown, you don’t know what you’re doing. Well, to be an autodidact means to overcome that fear. And just do it. On on the show’s Twitter, I reached out to Adam Savage because he, if you don’t know if it’s Adam Savage, he’s one of the myth busters from that Discovery Channel show.
He also so has YouTube channel called tested, he’s about to come out with a new TV show. He’s written books, he goes on tour, he does various readings and appearances he’s very, he’s he’s very proactive and very responsive to the maker community. But in any case, I reached out to Adam Savage on Twitter, because he truly has inspired me to just jump into the unknown. And of course, he’s not the only one. Parents are clearly the top choice on that one. But we won’t get into that much my personal history. But nevertheless, this kind of just willing to go for it not knowing what’s going to come out of it not knowing if there’s going to be anything beneficial to yourself or to society or to your bank account. It’s this willingness to just learn for learning sake. And that’s almost absolutely necessary to be an autodidact. And so the next piece of being an autodidact is one that I’ve heard from quite a few self help type people. And I’m so suspicious, and I couldn’t give a harder IRL to them. And that’s the notion of visuals, visualizing who you want to be or visualizing where you’re going to be once you achieve this goal.
There’s some truth to this and being an autodidact, you have to set a goal, or you’re at least attempting to achieve a certain level of knowledge or a certain kind of skill set. And so you should be able to see yourself as that person as that person with that set of knowledge, and then go for it. But the truth is, when you’re an autodidact, if you hit that particular goal, it’s not going to be enough, it’s not going to be the end of the road, you’re not going to get to that place and just stop. Hence why I’m suspicious of visualizing where you want to be because it’s an unknown unknown there, you you can’t possibly know where you’re going to be because you’re going to hit some arbitrarily set goal, and you’re just going to keep going. However, it is useful as a kind of intermediary goal setting. You can see certain goals along the way. So you see a goal that you’re like, I’m going to be this way, in three months, I’m going to have this set of knowledge or this skill set in three months, and then you just attack it and you get there.
And you said another one and another one, and another one. That’s part in my opinion, of being an autodidact. And so for the final piece, namely, a kind of fear. And in the last couple of episodes, we’ve been talking about spooky things, fear of automation, and a fear that comes with lacking critical thinking. Well, fear is something that can truly set you back and prevent you from becoming someone who was self taught. So in order to be an automatic, do you have to quash that fear you can’t let the fear of the unknown unknowns stop you in your tracks. Otherwise, hate to say it, but you’re not going to be an autodidact. You’re not going to get to where you want to be by yourself. And maybe you never will. So where does this leave us? This leaves us in the position where to be a truly good data scientist, a truly good data professional, someone in the data industry, you can but be an autodidact. Otherwise, you’re going to get left behind by the rest of the industry. So I hope you’ve enjoyed this episode and I look forward to speaking 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 email@example.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 a Creative Commons Attribution 3.0 license, writing, editing and production of the podcast is by your host, Jordan Bohall.