I stumbled across this TED Ed YouTube playlist called Think Like A Coder. It’s an amusing 10-episode video introduction for those new to programming and coding.
The series follows Ethic, a girl who wakes up in a prison, struck by amnesia, and thus without a clue how she got there. She meets Hedge, a robot she can program to help her escape and, later, save the world. However, she needs to learn how to code the Hedge’s instructions, and write efficient computer programs. Ethic and Hedge embark on a quest to collect three artifacts and must solve their way through a series of programming puzzles.
Episode 1 covers loops.
The adventure begins!
Episode 1: Ethic awakens in a mysterious cell. Can she and robot Hedge solve the programming puzzles blocking their escape?
Robert Martin’s book Clean Code has been on my to-read list for months now. Browsing the web, I stumbled across this repository of where Ryan McDermott applied the book’s principles to JavaScript. Basically, he made a guide to producing readable, reusable, and refactorable software code in JavaScript.
Although Ryan’s good and bad code examples are written in JavaScript, the basic principles (i.e. “Uncle Bob”‘s Clean Code principles) are applicable to any programming language. At least, I recognize many of the best practices I’d teach data science students in R or Python.
Knowing these won’t immediately make you a better software developer, and working with them for many years doesn’t mean you won’t make mistakes. Every piece of code starts as a first draft, like wet clay getting shaped into its final form. Finally, we chisel away the imperfections when we review it with our peers. Don’t beat yourself up for first drafts that need improvement. Beat up the code instead!
As I wrote about Project Euler and CodingGame before, someone recommended me CodeWars. CodeWars offers free online learning exercises to develop your programming skills through fun daily challenges.
In line with Project Euler, you are tasked with solving increasingly complex programming challenges. At CodeWars, these little problems you need to solve with code are called kata.
Kata take a test-driven development approach: the programs you write need to pass the tests of the developer who made the kata in the first place. Only then are you awarded with honour and can you earn your ranks and progress to the more complex kata.
Sounds fun right? I’m definitely going to check this out, as they support a wide range of programming languages, each with many kata to solve!
Python, Ruby, C++, Java, JavaScript and many other main programming languages are already supported, but CodeWards is also still developing kata for more niche or upcoming languages like R, Lua, Kotlin, and Scala.
A friend of mine pointed me to this great website where you can interactively practice and learn new programming skills by working through small coding challenges, like making a game.
CodinGame.com is an gamified learning community and website that allows you to learn new concepts by solving fun challenges. Pick from over 25 programming languages, including Python, C, C++, C#, Java, JavaScript, Go, and many more. In a matter of hours, you will work on hot programming topics, discover new languages, algorithms, and tricks in courses crafted by top developers.
2018 seemed to be the year of challengesgoing viral on the web. Most of them were plain stupid and/or dangerous. However, one viral challenge I did like: #100DaysOfCode
1. Code minimum an hour every day for the next 100 days.
2. Tweet your progress every day with the #100DaysOfCode hashtag.
3. Each day, reach out to at least two people on Twitter who are also doing the challenge
Many (aspiring) programming professionals competed in this challenge, sharing their learning journeys in domains from web development, machine learning, or data visualization.
With this blog, I wanted to share two of those learning journeys that stood out for me.
Machine learning
First, there’s Avik Jain’s 100 days of Machine Learning code repository on Github. Avik’s repository contains all learning activities he followed during the 53 days of programming he completed. Some of Avik’s entries really stood out, and I particularly liked his educational infographics:
Just look at the wonderful design and visual aids on this decision tree for dummies infographic, pseudocode and all:
Day 23: Decision trees for dummies. This just looks fabulous right?!
Although Avik didn’t seem to have completed the full 100 days, many others did.
Data visualization
I have blogged about Hannah Yan Han‘s 100 days of code project before, but she definately deserves another mention here. Her 100 days revolved around data science, data visualization, and storytelling using both R and Python. You can find her #100DaysOfCode Medium page here, and her associated Github repository here.
For example, one day Hannah explored where instant noodles come from, how they are served, and whether people like them or not.
What I found so great about Hannah’s project is that she picked a novel dataset every couple of days. Moreover, she used a extremely large variety of different visualization formats. All visuals were equally beautiful, but Hannah made sure to pick the right one for the purpose she was trying to serve. If you are interested in data visualization, you seriously should check out Hannah’s 100DaysOfCode Medium page.
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