Four Short Lessons From Learning Python

My product development process in a nutshell

Python is a GREAT tool for creative work.

Little did I know that in between working on certain concepts like Loops, Object Oriented Programming (OOP), and even Else/If Statements, ideas would just naturally come out. Creative ideas, product ideas.. only the noticeable difference was that the logic part was stronger. This time, I could actually imagine how it’ll work, not just the why and the what.

As a maker, the goal now is not just to be less dependent on code in making ideas happen but also other way around: Work towards the state where the idea (‘design’) will drive the code which will ultimately drive the product. Design will shape the technology. For designers, this lofty ambition has to be earned, and I believe learning how to speak to machines is the most obvious first step. Figma is not the only tool designers should leverage.

Screenshots of Kaggle and a Jupyter notebook I’ve started for cleaning the data

Finding good data is an exercise in resourcefulness.

It is incredibly difficult to attain a good quality of dataset. With tools like Kaggle, and all the other resources mentioned here, one can easily find alternatives. At least for building proof of concepts and MVPs, these platforms work. The reality is it may not be enough, and this where creativity comes into play.

It’s an imperfect system but I’ve learned that if you use your strengths to your advantage, the lack of a good quality of data shouldn’t be a blocker to making that vision a reality.

With Python, you get back what you put in.

Yes, there were bad days. There was definitely a narrow period where in I was ready to just quit and cut my losses. What got me through those days (and weeks) was just showing up and trying my best to ship something. Anything. I have never felt more dumb. In retrospect, that was great thing.

Whether it’s refactoring my code or applying a logic I’ve learned in class, or hell, just copying other people’s code just to continuously develop a muscle memory, small wins matter. In this case, small wins actually got me through those tough and frustrating times over, and over again. Do not underestimate small wins. If you try hard enough, they might just turn into the sum of an even bigger win.

The User Interface for the Dashboard I built using Python and Streamlit

One does not need to be an Engineer, officially, to effectively think like one.

It’s a superpower, not unlike Design and it starts by asking questions. Ask enough questions, and maybe just maybe, you’ll end up with the right ones. And again, just like Design, this takes a lot of practice. World class intuition development and technical skillset mastery is a lifelong pursuit. How does it work? Why does it work the way it works? What is the system behind it?

Because of learning python, I’m training myself to ask those questions more and more everyday. To find answers, yes. But more importantly, to be a little more more literate with how the world works, one system/product at a time.

The author is a User Experience Designer and a Qualitative Researcher who recently concluded an Intro to Python Bootcamp. Many thanks to General Assembly and Craig Sakuma. She would highly recommend the course for anyone who wants to learn Python and a little bit of Data Science.

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