What’s New at CFI | Getting Started with Python

Meeyeon (00:09)
Hi everyone, and welcome back to another episode of What’s New at CFI. Today I am joined by Joseph, one of our subject matter experts, and my personal dongsaeng, which if you are Korean, you’ll know what that means.

Today, we’re talking about one of Joseph’s latest courses, and it’s called Getting Started with Python. So let’s start at the very top. What’s the big idea behind getting started with Python?

Joseph Yeates (00:36)
Yeah, well, I guess thanks, Meeyeon for having me here today. Excited to talk about Python. And yeah, for getting started with Python, I mean, I think really, Python is really just such a popular programming language in the data analysis space, where we’re sort of my expertise and experiences from, but really throughout finance and really every sector, but finance for sure and data analysis. And there’s tons of interest in learning Python.

And we just really wanted to focus on that getting started piece, like what’s in the title. You know, it can be intimidating, just opening up a notebook or a Python development environment. And when you don’t really know what to do, you might just switch off or decide it’s too challenging for you, or you don’t want to put the time and effort in. So we wanted to pull together more of a gentle introduction before you can jump into more, ⁓ more advanced topics and more advanced scenarios.

Meeyeon (01:31)
So it sounds like this is not gonna be one of those, know, it is a CFI course, so it’s not necessarily gonna be Python for programmers, but it’s a more real world business analysis type of course. Maybe you could share with us what it was like for you when you first started learning Python. And did you have any of those kind of lessons learned and all the…

struggles that you might have had when you were first learning the language. Did you take any of those nuggets and put them into this course?

Joseph Yeates (02:06)
Definitely. Yeah, think learning Python and other programming languages that I use, I was very sort of self-taught or learning just enough to get whatever was in front of me done. So, you sort of learn a lot in this one area, and then you take a couple of steps back and you go into a different area, and then this doesn’t make sense. So then you go and pick up something else. So, you know, that took me quite a few years to get up to speed and fairly

basic and standard Python skills. But yeah, this course takes those years of experience takes that sort of traversing journey. And I’ve really tried to break it down into, okay, what can we focus on first, and what’s going to serve you well moving forward, so you can really jump off in a bunch of different directions after this course.

Meeyeon (02:57)
And if we’re giving our listeners a preview into this course, can you give us a quick walkthrough of maybe not necessarily, you know, chapter by chapter, but what the course covers overall and what the main topics and learning outcomes are?

Joseph Yeates (03:12)
Yeah, yeah, for sure. So we really tried to focus on some of these core concepts and foundational building blocks, if you will, of Python, really applicable, I think, to lots of different programming languages, but specifically to Python. And going and looking at things like variables, how to set up your data with data types, different data structures available, and how to start manipulating some of these things.

All trying to use really practical real world scenarios so that really the information you’re learning is useful right away. It’s not just this theory that you then get to do the fun stuff later. We’ve tried to make it really applicable upfront. ⁓ But it’s all these really foundational things that you can use no matter where you choose to go with Python.

Meeyeon (04:01)
So, for someone who’s used to Excel, which I think is going to be a large part of our CFI audience, especially everyone that’s taken the FMVA, we’re all used to living in Excel. So most of us, think, at least from the FMVA and CMSA realm, are quite new to coding. How do you think, for those of us who are mostly familiar with Excel, how does Python complement or enhance what we already do?

Joseph Yeates (04:28)
So I think there’s two main things come to mind with there is that with these Python courses, but we’re getting started in Python, we’ve really tried to build everything using tabular data structures as much as possible. So if you think of those columns and rows from Excel and maybe just how you think of your data and data structures and how you do things, we’ve tried to incorporate those same elements into Python to sort of make it that

bridge between programming and really typing out all the commands that you want to do. But you have that frame of reference already from Excel. And I think this, second thing, know, Python complimenting Excel skills, previously they were maybe quite separate and they were separate roles and separate skill sets. And over the last five to 10 years, I’d say they’re just becoming closer and closer and closer to a point now where Python is fully integrated into Excel

out of the box. Like a lot of the things that we cover in this course, we can execute within Excel just natively. So I think for users moving forward, learning Python and being familiar with Python as it becomes even more integrated into Excel can really just take your data analysis, data manipulation to the next level.

Meeyeon (05:50)
And if there is one thing that you think kind of surprises learners, ⁓ what do you think surprises learners the most when they first start using Python?

Joseph Yeates (06:01)
I think I’ll share a good thing and a bad thing, a good surprise and a bad surprise. So I think the bad surprise maybe or a surprising challenge is it does take quite a lot of setup. When you’re learning and taking courses, we do try and make it as streamlined and easy as possible to just get to the coding. But when you’re doing it in your own environment, on your own data, just getting set up can be a pretty big barrier to entry.

I would say. But on the other hand, the good surprise, the pleasant surprising part of Python, think, is just how readable the syntax is. Like I feel if someone had not really experienced Python before, and they’re given a script of Python doing some data analysis, I think most people would be able to look at it and have a pretty good idea of what’s going on and what the user’s trying to achieve with that block of code and with that Python. So I think it’s sort of…

maybe more challenging to get set up, but then once you’re set up, it might be a little bit more simple to get up and going or become more familiar with the language than you might think.

Meeyeon (07:09)
Yeah, that sounds like it’s going to be a very different experience, probably a bit more of a pleasant one than I had with my first foray into programming languages. When I was in portfolio management, I worked in fixed income and the first language I learned was, I think it was just like C++. And I found that to be very unintuitive and I did not do well with it, but I was able to do what I needed to do. And in that same vein, where do you think learners usually kind of get stuck?

Joseph Yeates (07:28)
Yes.

Right.

Meeyeon (07:39)
And how did you try to make that easier in this course? Because as with learning even just a verbal language that is challenging on its own, but when we talk about a programming language, where do you think people usually kind of just get stuck? And how do you think that this course is going to make that a little bit easier for them?

Joseph Yeates (07:58)
Yeah, think speaking from my personal experience, kind of ties back into what I was saying of being self-taught. And I think people coming into Python a lot of the time are self-taught or they’re picking up a process or a script that someone else has written, and it breaks. So then you need to be the one to fix it or understand what’s going on.

Meeyeon (08:17)
So as with learning, I think any language, whether it is, you know, like English, French, Spanish, ⁓ you face similar challenges and hurdles with programming languages. Where do you think learners usually tend to get stuck when it comes to learning Python? And how does this course, you think, alleviate some of that stress and like getting stuck?

Joseph Yeates (08:40)
Right. Yeah. So I think this ties back into one of my earlier points about being self-taught is that when, when you’re just trying to get by or when you’re just trying to fix something that comes up with Python and you’re really jumping into it, you sort of go down these paths without much thought of going into what you’re learning or why you’re learning it in what order. And, and you can get stuck and it can get frustrated. And sometimes that’s because you’re doing sort of a 400-level topic before you know some of the

100-level foundational aspects of the language or of the specific thing you’re trying to do. So I think with a course like getting started with Python, what’s nice is it gives that really level set of these things like variables and data structures, all of which can result in really common errors that you can be banging your head into the wall. And it’s just, I wasn’t aware of this simple thing. Like, my data is in the wrong data type. And it means I can’t do this.

really complex calculation that actually works, but some of my numbers are stored as text as an example. So some of these foundational items are super important and I think can help really troubleshoot and alleviate some of those ⁓ head banging into the wall moments.

Meeyeon (09:56)
And of course, with Anything CFI, we are very focused on hands-on practical learning, and there’s some practice exercises that are built into this course. How important do you think it is for our learners to follow along in Jupyter Notebooks rather than just watch the videos?

Joseph Yeates (10:14)
It’s very important, the most important. think with programming in particular, hands-on and actually doing stuff is how you learn. is making the mistakes, learning from your mistakes, actually typing things out, seeing how things work. That’s the most important thing. I know that’s true with lots of different subject matter and lots of different CFI courses.

But I would stress that for a technical course like this, where you’re learning a programming language, you need to be actually doing it to learn and get that repetition. Similar to learning English or French or any other language, you need to be speaking and hearing and practicing to really get better.

Meeyeon (11:01)
Yeah, someone once said to me, it is not a spectator sport. Like you have to be involved and you have to get your hands dirty and practice. Can someone really, you think, go from zero Python knowledge to analyzing their own data after this course?

Joseph Yeates (11:10)
Totally.

I would say yes to at least yes to a certain extent, doing sort of some of the foundational, ⁓ at least setup of their data and getting some surface level insights, I would say for sure, I know that’s it’s a lofty target to go from zero to a real world application. But that’s really what we try to build into the course that makes everything super applicable. And I think, yeah, with the expectations of,

of a nice simple analysis and sort of simple data set. Absolutely. think a lot of learners will be able to jump into that.

Meeyeon (11:58)
And for anyone that’s listening right now that is curious but on the fence and nervous to start learning Python, do you have any encouraging words that would tip them over?

Joseph Yeates (12:12)
I think just do it. What’s the worst that could happen? I know it can be, I know it can be hard and it can be challenging sometimes, but I feel particularly for people coming over from the Excel world into Python. Excel can be simple, but it can also be super complicated. And I would say the same thing with Python. It might be a little bit more challenging upfront, but just like how there’s some simple things and more complicated things in Excel.

I would say it’s the same in Python. And in this course, we’ve really tried to focus on building that repetition and building that expertise in some of those more simple things. So I think you can definitely do it. And this is a great starting point.

Meeyeon (12:53)
So if you’ve been on the fence about learning a programming language and you’ve been on the fence about Python, this course is going to make it super easy for you to get started. We’ve got more courses related to this topic coming up. So keep an eye out for our Python follow-ups. But for now…

This has been us, has been Meeyeon and Joseph from CFI, and we will talk to you guys next time.