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Skills like coding scares a lot of people. The media has made it seem like writing computer code is a genius-level activity, as weird symbols race across the screen and techno music blares in the background.But the truth is that, coding is actually pretty easy.I’m not saying this to dismiss the work of brilliant programmers. A skill can simultaneously be fairly easy to get the basics in, while also being really difficult to master. Everyone learns to write, few people learn to write well. There’s no contradiction, therefore, in saying that basic literacy is an “easy” skill to acquire (in that the vast majority of us are able to do it), without dismissing the efforts of talented writers.Nor am I saying this to mock people who are trying to learn programming and find it frustrating.Rather, I say coding is easy because I believe that almost all people, even if they don’t see themselves as particularly smart, have the ability to learn to write simple programs. That they don’t is mostly due to some structural barriers than any intrinsic difficulty with the skill itself.My Experience CodingI started learning how to write code since I was 14. I’ve read a couple of O’Rielly books on programming, took even free courses on Coursera and Udemy. Watch thousands of hours on programming related videos on YouTube. I remember even working through the content of a Computer Science Degree online (which is totally unnecessary if you want to learn to code,by the way).If you take a closer look, in some ways... my background may seem to disqualify me about making statements on the ease of coding. However, I can say without a single doubt, that subjects like Accounting, Physics, Engineering and even Law are more difficult than programming.Most math you learn in high-school is more difficult too, believe it; although you usually get wayyyyy more practice with algebra than writing code, which leads to a misperception as to which is more difficult.Why Coding Feels HardLearning to code is hard for a couple reasons:Installing new languages can be super frustrating. This is the first activity for a wanna-be programmer. This can create the misperception that programming is really hard because newbies extrapolate the difficulty of getting set up to how it weill be every moment after.Also, there are waayyyyyyyy too many languages, frameworks tools, libraries and plug-ins. Starting programming is super overwhelming because there are a stadezillion things to learn and you have no idea where to start.The first moments of programming are the hardest. Getting set up is annoyingly difficult and often requires learning a new way of working with computers even before you write a single line of code.Consider the instructions for installing most languages:“Open the terminal or command prompt. Type in a case-sensitive exact set of instructions to download and install the language. Use GitHub. Homebrew. Versions matter too. Are you running 32 or 64 bit? ‘Cause if you’re not sure it will crash with a cryptic error message and you’ll feel like an idiot.”These tools are learnable, like everything else, but they reinforce the impression given by the media that coding is mostly using elite tools with weird, unfriendly user interfaces. When people see coding they imagine parsing the green-streaming letters on computer screens like the movie, The Matrix; whereas the truth is a lot more like following a recipe along step-by-step.How Do You Get Over the Initial Difficulties?There’s a few ways you can do this. My favorite is to just go to the language or technology official documentation, that will tell you exactly how to set up step-by-step.Alternatively, you can dive into internet tutorials (why do you think platforms like YouTube, Quora exists?), but recognize that sometimes they are aimed at already-proficient programmers, who know what OOP and GitHub are, and are fluent with writing commands into Terminal.If you get one of these, you can try to follow it, but don’t feel bad if you screw it up. It’s frustrating and it doesn’t mean all coding will be like this.Another option is to avoid setup at all. Just use some coding tutorial website that teach you to code without needing any installation. I like this too, but sometimes you can’t actually build the thing you want to build with these apps. However, if you hate the setup, that’s where I’d start.Most important, however, is to remember that I told you this. When you try to learn to code, it will be frustrating to get set up, and just accept that this is a small price to pay. Soon it will be easier and you’ll do stuff that is cool. Don’t feel dumb because you get stuck here, I still do and I’ve been writing code for years.What Language/Framework/Library Should I Start With?This seems like a good question to ask, but, I’d argue, it’s actually the wrong way to think about learning programming.First, despite the fact that programmers often boast about how many languages they know, recognize that most languages are only superficially different. Yes, I know all about language design, so don’t tell me about the importance of scripting versus compiling, or whether a language is strongly or weakly typed. Those things matter, but they’re details.The basics of nearly all languages and tools are the same. Variables. Loops. Functions. Pointers. Data Types. OOP. Modules. These concepts exist in almost all programming languages. If you pick a mainstream language, you’ll learn these in mostly the same way, so it doesn’t matter if you pick Python, JavaScript, C++, Java or even PHP.The place languages do matter is what you want to use them for.Want to write iPhone apps? Swift or Objective C are the languages of choice. Need to create web pages? JavaScript is going to come in handy. Yes, you can use almost any language for any task if you tinker with it and get the right plug-ins. However, some languages are easier to get started with certain types of projects than others.Therefore, the first question to ask is not: which language should I learn, but, which project should I start with?What Should Be Your First Project?I recommend starting your programming adventure, even before you write a single line of code, with a decision about a concrete programming project you’d like to create.This serves a couple purposes:It narrows down the language/framework choices considerably. Once you know you’re building a website, you’re already leaning towards tools that were designed with that goal in mind.Everything you learn is connected to a destination. Transfer of learning is notoriously difficult. Learning directly by building, works better than learning something and just hoping it will help you later.You can work on something you think is cool. If you think it would be cool to make an interactive website, do that. If you’d prefer a game, do that. If you’d prefer to automate some tedious work, do that instead. Do what you feel is cool and you’ll be motivated to stick to it.In general, smaller is better when it comes to projects. Deciding to start with making the next Google is ambitious, but probably will get you stuck in the weeds before you make much progress.If your true ambitious are huge, it’s often best to work on a toy project first. Many experienced programmers still do this when they are entering a new territory of programming. Toy projects take the essential ideas of programming, but turn it into something you can do in a few days or weeks, instead of years.Examples of good projects include:A basic terminal text-adventure game. No graphics, but still requires learning concepts like loops, variables, input-output processing.A simple website. Start with just displaying a static page. Maybe add in comments, users, photos or interactive elements as you learn more.A simple app. What’s something dead-simple you’d like to have on your phone? It can be stupid to start, don’t worry.A script for automating a tedious task.In general, programs are easier when they involve no multimedia content (websites are a bit of an exception), so if you’re making a game, for instance, a text game tends to be easier than one with graphics, if only because making all the graphics can take time.Similarly, different core activities have different difficulties. Arithmetic and simple calculations done repeatedly are easiest. Processing text for exact patterns is a bit harder. Processing text for vague patterns is harder still. Processing, speech, photos and video is even harder.If you do end up picking an initial project that turns out to be super difficult, it’s okay to scale back. “Make an application that calculates my mortgage payments” is much, much easier than “Make an application that can tell you what someone’s hairstyle is from a photo.” It’s often not obvious that this is the case in the beginning, so don’t worry if you accidentally pick a “hard” problem to start with, you can adjust it later to something easier.Which Resources Should You Use?Once you’ve picked a project, the next step is to get some resources to help. This is a step many people worry over endlessly, but like the language choice, it’s a lot less important (and depends more on your goals) than you think.I won’t list specific resources, because there are so many good ones that my suggestions are going to leave out some of the best. Instead, here’s three strategies for finding good resources:Get a book that teaches you the language + project you want. There should be a computer section in your city’s bookstore or library, you can just pick any of those. I personally like O’Reilly (they publish the best software development books), but there are lots of good ones. (If you haven’t figured out which language yet, just DuckDuckGo your type of project and look for suggestions.) I read the Self-taught programmer by Cory Altoff, the first time I wanted to learn Python.Attend a MOOC. Coursera, edX, MIT, Harvard, FreeCodeCamp and others all teach computer programming online. Once again, the thing that matters most isn’t the exact class, but whether it teaches the language/project domain you care about.Stressing over which book or course to pick is the wrong thing to worry about. The main thing to do is to use the book or course to learn enough to start tinkering on your project, not to master programming on its own. Starting your project before your ready is definitely the way you should feel about it.Do What Real Programmers Do and Ask DuckDuckGo/StackOverflow/GoogleOnce you actually get started writing code, you’re going to encounter many, many situations where you either don’t know how to do something, or you learned how to do it before and you’ve forgotten.In these situations, you should do what real programmers do: ask DuckDuckGo/Google/StackOverflow. This isn’t a shameful activity, but a part of real programming. I’ve been coding for years, but I always forget silly syntactical things and so I find myself duckduckgoing regular expressions over and over again. It’s not bad, it’s just part of the process.Once you’ve gotten yourself installed, you’ve learned a bit with your book to know the basics and have started working on your first project, you’ll learn the rest by googling and adding to your library of programming knowledge. Computer science theories, detailed understandings of the language you’re working with or advanced design patterns can wait until you’ve finished a few real projects and feel like you can code something.Notice #1: Don’t Copy-and-PasteA first piece of advice when it comes to this step is to never copy-and-paste. Copy-and-pasting is bad because you don’t try to understand the code you’re copying. If you have to transcribe, in contrast, you naturally ask yourself, “why this? why not something else?” Even if you don’t have a great answer immediately, typing things for yourself will open your mind up to the answer whereas copy-and-pasting shuts down thinking.Notice #2: Try it Yourself Before Looking for a SolutionA second piece of advice is to always try to solve something yourself before looking up how someone else does it. Most problems have many, many ways they can be solved. The challenge is that expert programmers often know a particularly concise, clever way, but that often isn’t the “obvious” way.This can lead to a trap where you see a clever solution that employs tricky syntax, think that there was no way you would have guessed that solution, and believe you couldn’t have solved it on your own. That’s usually not true, yet it’s an unfortunate side effect of looking up solutions before trying to find your own.Summary of AdvThisisting up is frustrating.

Learning to Code: Is It Really That Difficult?

Anyone I asked for advice was against me quitting the stable job to explore completely uncharted territory, and that too with a child. But eventually, I quit.

How I Became a Developer in 7 months After 5 Years of Unrelated Experience

Acquiring a new skill is good but knowing exactly which path to take in advance is best. For every decision taking to learn something new, there is always this “where” or “what” question. Where will I start, what should I do, where will I get material, what so ever be the case there is always a “where” or “what” question. Knowing exactly which path to take as a newbie in technology is almost impossible unless you follow a strict guide from a mentor or any other source. This article is more like a guide through the walk of a self-taught web developer.

The Path of a Self-Taught Developer

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Midnight Opens Redemptions for 4.5B+ NIGHT Tokens After Record-Breaking Distribution Event

Learn why Zero Trust is vital in 2025, how AI-driven attacks and regulations increase the stakes, and practical ways to protect your business today.


Zero Trust Security Goes Mainstream as Breach Costs Hit Record Highs

Samsung Electronics, Hyundai Motor, and SK Group have announced that they are planning new domestic investments, CNBC reported on November 16. 

South Korea Secures Record Commitments From Samsung, Hyundai, and SK

Recognition we believe underscores global customer trust and proven product excellence for security teams evaluating NDR solutions

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Removing gender from AI models doesn’t erase bias. Learn how systematic stereotypes persist in recommendation systems despite feature removal.

Can We Ever Fully Remove Bias from AI Recommendation Systems?

Quantitative case study revealing how gender bias forms in podcast recommendation systems — and what it means for ethical AI.

That Time We Found Gender Bias Hidden in a Podcast Recommendation System

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Discover a framework to detect and evaluate representation bias in latent factor recommendation systems using real-world podcast data.

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Uncover how hidden stereotypes shape AI recommendations and learn how new frameworks can detect and reduce bias in machine learning models.

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Reeco's stories on HackerNoon

Learning to Code: Is It Really That Difficult?

How I Became a Developer in 7 months After 5 Years of Unrelated Experience

The Path of a Self-Taught Developer

HackerNoon Projects of the Week: Pantry Pilot, RecomendeMe & Charmpay

This Model Fixes Noisy Speech Recordings Before Your Transcriber Ever Sees Them

The Recommendation Engine Behind Your Cart: Design, Build, Maintain

RecomendeMe Earns a 56 Proof of Usefulness Score by Building a Human-First Recommendation Platform

Healthcare Disaster Recovery: What You Need to Know

The Discovery Gap: Why ChatGPT Knows Your Startup But Won't Recommend It

11 Best Mobile App Development Companies Recommended For Enterprises in the USA in 2026

Why Does Real-Time UPDATE Synchronization Require Two Records? A Full-Chain Breakdown in SeaTunnel

Flight Recorder: A New Go Execution Tracer

When Public Data Disappears: The Quiet Restoration of SSN Issuance Records

How We Migrated a Billion-Record Database With Zero Downtime

Midnight Opens Redemptions for 4.5B+ NIGHT Tokens After Record-Breaking Distribution Event

Zero Trust Security Goes Mainstream as Breach Costs Hit Record Highs

South Korea Secures Record Commitments From Samsung, Hyundai, and SK

ThreatBook Peer-Recognized as a Strong Performer In the 2025 Gartner Peer Insights

Evaluating Attribute Association Bias in Latent Factor Recommendation Models

Can We Ever Fully Remove Bias from AI Recommendation Systems?

That Time We Found Gender Bias Hidden in a Podcast Recommendation System

A Practical Framework for Auditing Bias in Recommendation Algorithms

Detecting Hidden Bias in AI Recommendation Systems

Quantifying Attribute Association Bias in Latent Factor Recommendation Models

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Reeco Hackett scores twice as in-form Lincoln see off Barnsley

Reeco Hackett scores twice as in-form Lincoln see off Barnsley

Reeco Hackett scores twice as in-form Lincoln see off Barnsley

Reeco Hackett scores twice as in-form Lincoln see off Barnsley

Reeco Hackett scores twice as in-form Lincoln see off Barnsley

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