How to Make Learning to Code Easier by Focusing on the Fundamentals

It’s the beginning of the year again, and perhaps you’re still struggling to learn that programming language. We’ve all been there. Let me share a story from my own journey.

In 2016, I thought I wasn’t cut out for programming. After months of trying and failing with my first language, I came to a conclusion: I wasn’t smart enough. I thought some people were naturally gifted, while others, like me, simply weren’t meant for programming.

I gave up several times, convinced I didn’t have the talent needed to succeed.

Fast forward to today eight years later. I’ve become proficient in several programming languages. Looking back, I realize programming doesn’t come naturally to anyone. The difference between those who seem “gifted” and those of us who struggled is simple: it’s all about having the right foundational knowledge.

Programming is like walking into a movie halfway through you can’t understand what’s happening because you missed the beginning. The same applies to programming. You can’t build an advanced calculator app without understanding basic data types or algorithms.

Here’s the truth: programming isn’t inherently difficult. Most beginners struggle because they skip key foundational steps. Without these prerequisites, programming can feel like trying to swim in the deep end without first learning how to float.

But don’t worry I’ve got you covered. By the end of this article, you’ll know exactly what these prerequisites are, how to develop them, and why they’re the key to making programming click for you.

Here’s what we’ll cover:

1. Why Programming Feels Hard – Hint: It’s Not About Talent

2. The Prerequisites You Actually Need

3. Data Structures: Taking User Input

4. Algorithms: Performing Computations

5. Programming Languages: Displaying the Output

6. Additional Skills

7. How to Build the Right Foundations: Practice, Practice, Practice

8. Final Thoughts

Why Programming Feels Hard – Hint: It’s Not About Talent

Let me pick up my story again. By 2018, I was becoming a confident developer. I could build basic websites, fetch data from a database using APIs, and display it on the screen. I thought I had programming figured out.

Then came my first job interview.

During the interview, I was asked a seemingly simple question: “What happens when you type www.google.com into the address bar and press Enter? You have 30 minutes.”

I paused, thought for a moment, and gave my best answer. I spoke for maybe five minutes, then the interview ended.

Later, I Googled the question out of curiosity. What I found shocked me. The question wasn’t just about typing and entering a URL, it was about networks, servers, DNS lookups, HTTP requests, rendering engines, and more. That’s when it hit me: I had barely scratched the surface. There was so much foundational knowledge I was missing.

That day, I realized programming isn’t just about fetching data from a database or making a website look good. It’s about understanding the layers beneath the surface. If you’re curious, I didn’t get the job. In fact, I never heard back from them. Honestly, I wouldn’t have hired me either.

Now, think about that interview question: Could you confidently explain what happens when you hit “Enter” on www.google.com?

If you’re like I was back then, probably not. But here’s the good news: If I were asked that same question today, I could speak on it for an hour. Heck, I could even write a 1,000-word article about it.

The Real Problem Isn’t Talent

Here’s the key takeaway: programming success isn’t about talent or intelligence. If you try to learn programming without the right preparation, you’ll keep hitting a wall of frustration.

So, no—it’s not talent you lack. It’s preparation. And the good news? Lack of preparation is something you can fix.

The Prerequisites You Actually Need

To understand the prerequisites, let’s take a step back and consider what a computer is actually for. At its core, the main purpose of a computer is to:

1. Take user input,

2. Perform computations, and

3. Display the output.

Every piece of software or program ever developed revolves around these three tasks. As a programmer, your role is to create software that performs these functions properly.

To do this, you need to build your skills in a way that aligns with these tasks. This means learning about data structures and algorithms, and then diving into a programming language. Let’s dig into each of these skills more deeply.

Data Structures: Taking User Input

So, users interact with your software, whether they’re clicking buttons, filling out forms, or uploading files. And guess what? All that interaction creates data that you, the developer, need to manage. But how do you do that without going crazy? That’s where data structures come in.

What Are Data Structures?

Think of data structures like special containers for your data. But not just any containers – they’re the kind that let you quickly grab, change, and organize your data in the most efficient way possible. Without them, managing user input would be like trying to store your clothes in a messy pile rather than a neat closet. Not fun, right?

A Few Data Structures You Should Know

There are tons of data structures out there, but let’s talk about a couple that are absolute essentials:

1. Arrays

Arrays are like simple, ordered lists. Imagine a row of boxes, each labeled with a number (index). You can put something in each box, and when you want to grab something, you just tell the system the number of the box. Super easy! It’s like a list of your favorite songs, where each song is numbered in order.

2. Hash Tables (or Dictionaries)

Hash tables are the cool kids of the data structure world. Instead of organizing data by number, they let you organize it by keys, which are like labels that help you find things super fast. If you had a list of customers, you could use their customer IDs as the “key” to look up their info. Think of it like a phone book—rather than flipping through pages, you jump straight to the person’s name based on how the names are organized (likely alphabetically).

Why Should You Care About Data Structures?

Good question! Here’s the deal: first of all, data structures help you organize your data in an intelligent way that makes sense. They keep things neat and make them easy to access. No more digging through a pile of data.

Second, data structures can make your apps faster. With the right data structure, you’ll be able to retrieve, modify, and sort data in the blink of an eye.

And finally, they help you solve problems like a boss**.** Whether you need to sort stuff, search through a lot of data, or handle some complex information, data structures are your go-to solution.

Example: Storing and Finding Customer Names

Okay, let’s say your app needs to store and retrieve customer names. You could do this in two ways. Let’s compare how an array and a hash table would handle this task.

1. Using an Array:
Imagine you’ve got a list of customer names, and they’re stored in a nice, neat array:

customers = ["John", "Jane", "Emily", "Michael"]

If you want to grab the name of the person in the third spot (Emily), you can just point to the third index like this:

print(customers[2])  // Output: Emily

Arrays are perfect if you have a simple, ordered list and you need to grab items by their position.

2. Using a Hash Table:
Now, let’s say you want to store customer names but also have a unique ID for each one. This is where a hash table (or dictionary) comes in handy. You use keys (like customer IDs) to quickly find their names. It’s much faster than searching through an array.

Here’s what it might look like in action:

customers = { 101: "John", 102: "Jane", 103: "Emily", 104: "Michael" }

Now, if you want to find the customer with ID 103 (Emily), you just look up the key:

print(customers[103])  // Output: Emily

Hash tables are awesome when you need to look things up fast. No searching, just straight to the point!

Ready to Dive Deeper?

If you’re pumped to learn more about data structures, here are some resources to help you level up:

Algorithms: Performing Computations

Okay, so you’ve got your data. Now what? Well, you need to process it—and that’s where algorithms step in. Think of algorithms as a set of instructions, kind of like a recipe, that tells your computer how to solve a problem or complete a task, step-by-step.

Why Learn Algorithms Before You Learn a Programming Language?

Before you dive into learning a programming language, it helps to first learn algorithms. Here’s why: algorithms teach you how to think like a problem-solver. They help you break down challenges, think logically, and tackle them systematically. And when you know your algorithms, you’re not just memorizing syntax – you’re also learning how to solve problems efficiently. That makes programming a lot easier.

Let’s Dive Into Some Cool Algorithms

There are a ton of algorithms out there, but let’s keep it simple for now with a couple of the most popular ones. These will get you started and make your code run smoother than ever.

1. Bubble Sort: The Basics of Sorting

Bubble Sort is the beginner’s go-to algorithm for sorting. It’s simple—kinda like flipping pancakes. You start with the first two elements in the list, compare them, and if they’re in the wrong order, you swap them. Then you move to the next pair and keep doing that until everything is in order.

Here’s how it works:

Imagine you’ve got a list of names that need to be sorted alphabetically:

John, Sarah, Anna, Jake, Emily

Bubble Sort will go through the list, comparing two names at a time, swapping them if they’re out of order. It repeats this process until the list is sorted.

At the end, your list will look like this:

Anna, Emily, Jake, John, Sarah

It’s simple, but not the fastest for long lists.

2. Quick Sort: Speedy and Smart

If Bubble Sort is like a slow and steady turtle, Quick Sort is the speedy rabbit. It’s much faster, especially for larger data sets. Quick Sort is a “divide and conquer” algorithm—it breaks the list into smaller chunks, sorts them, and then puts everything back together.

Here’s how it works:

Let’s take that same list of names and use Quick Sort:

John, Sarah, Anna, Jake, Emily

First, pick a pivot—let’s say Jake. Now, split the list into two parts:

Now, you repeat the process for each group. Keep picking pivots, splitting, and sorting until each group is small enough to be sorted easily. Then you just put everything back together, and voilà! Sorted list:

Anna, Emily, Jake, John, Sarah

Quick Sort is much faster than Bubble Sort, especially when you’ve got a lot of names to sort.

Again, there are many more algorithms to learn, but this should give you the basic idea of how they work and why they’re useful.

Why You Should Care About Algorithms

So why does any of this matter? Here’s the deal: first, algorithms help you solve problems more easily by breaking them down problems into manageable steps.

Second, they make your code faster. With the right algorithm, you can make your code run like a sports car—fast!

They also allow you to manage big datasets more easily. Some algorithms, like Quick Sort, can handle large sets of data in no time, which is crucial when performance matters.

Want to Get Better at Algorithms?

If you’re hungry for more algorithmic goodness, here’s where to go:

And if you want to dive deeper, here’s a free 48-hour course on the freeCodeCamp YouTube channel on Data Structures and Algorithms.

Programming Languages: Displaying the Output

Finally, we get to programming languages. This is where most beginners start and it’s often why they struggle. Without a solid grasp of data structures and algorithms, programming languages can feel like trying to run before you can walk. You can learn the syntax, but without understanding the fundamentals, you’ll find it harder to write effective code.

Why Programming Languages Should Come Last:

Once you understand how to manage input (data structures) and process it (algorithms), learning a programming language becomes much easier. You can go beyond worrying about memorizing syntax you may not understand, and start applying logic and solving problems. Programming languages are the tools you use to implement your algorithms and data structures.

Which Programming Language to Learn:

When it comes to picking a programming language, it’s important to align your choice with your goals. The language you choose should be based on what you want to build and your career path.

Here’s a breakdown of some common choices:

• JavaScript: If your goal is to build websites or web applications, JavaScript is essential. It runs in the browser and allows you to create dynamic and interactive websites. JavaScript also has a wide range of libraries and frameworks (like React, Node.js, and Vue) that can speed up development.

• Python: Known for its simplicity and readability, Python is a great choice for beginners. It’s widely used in data science, web development (with frameworks like Django and Flask), and machine learning. Python’s syntax is clean and easy to understand, which makes it perfect for beginners focusing on building strong foundational skills.

• Java: If you’re interested in building large-scale, enterprise-level applications, Java is a solid choice. It’s a statically typed language, meaning you define variable types explicitly. Java is commonly used in Android development and large backend systems.

• Swift: Swift is a great language for iOS app development. If you want to build mobile apps for the Apple ecosystem (iPhone, iPad, etc.), Swift is the way to go. It’s fast, modern, and integrates well with Apple’s software development tools.

• C#: If you’re planning to work with game development, especially with Unity, C# is your best bet. It’s also used for enterprise applications, web development (via ASP.NET), and desktop apps.

How to Choose the Right Language for You:

The best way to choose a language is to consider what excites you and where you want to focus your efforts. Don’t worry too much about finding the “easiest” language – just focus on one that aligns with your interests.

For example, if you’re excited about building websites, JavaScript might be the best place to start. If you’re interested in mobile apps, Swift or Kotlin could be a better fit.

Once you’ve picked a language, don’t stress about mastering every feature. Start with the basics and build projects that interest you. As you practice, you’ll naturally pick up more advanced concepts and techniques. The goal isn’t to become a master of syntax but to learn how to think like a programmer and solve problems effectively.

Here are some tips for getting started:

1. Start with Basics: Get comfortable with basic syntax and constructs. Learn how to write loops, conditional statements, and functions in your chosen language.

2. Build Simple Projects: Apply what you’ve learned by building small projects. If you’re learning JavaScript or Python, for example, try building a simple to-do list app or a calculator. These types of projects help solidify your understanding.

3. Understand Libraries and Frameworks: Once you have the basics down, dive into libraries and frameworks that can help speed up development. For JavaScript, this might mean learning React or Vue. For Python, it could mean exploring Django or Flask.

Helpful Resources for Learning Programming Languages:

Additional Skills

While mastering the fundamentals of programming is essential, there are other skills that can significantly boost your development journey. These include problem-solving techniques, debugging, and version control. These skills might not seem as glamorous as learning a programming language, but they are just as important.

Why These Skills Matter:

Even if you know the syntax of a language, you’ll still face challenges when writing real-world applications. Problems like bugs, performance issues, and collaboration with other developers are inevitable. That’s why these additional skills are so valuable as they help you tackle these challenges more effectively.

1. Problem-Solving:
Problem-solving is at the core of programming. It’s not enough to know how to write code – you also need to know how to break down a problem and figure out the best way to solve it. A good programmer typically spends just as much time thinking about the problem as they do writing the solution.

• Breaking down the problem: Start by understanding the problem. Ask questions like: What am I trying to achieve? What do I already know? What inputs do I have, and what do I expect as the output?

• Dividing it into smaller parts: Once you have a clear understanding, divide the problem into smaller, manageable pieces. This helps you focus on solving one part at a time rather than feeling overwhelmed by the entire issue.

• Looking for patterns: Often, problems in programming can be solved by recognizing patterns or using similar approaches you’ve learned before. Don’t be afraid to reuse code you’ve written or adapt it for a new task.

2. Debugging: No code is perfect, and bugs are inevitable. Debugging is the process of finding and fixing these bugs (problems in your code that cause it to mess up or not run). It’s a skill that every programmer needs to learn because it helps you maintain and improve the quality of your code.

• Using print statements: A simple and effective debugging technique is inserting print statements (or logging) in your code. This allows you to inspect variables and understand what’s happening at different stages of your program.

• Using a debugger: A debugger is a tool that allows you to step through your code line by line. It’s especially helpful when dealing with more complex bugs. Many programming environments, like Visual Studio Code or PyCharm, have built-in debuggers.

• Checking for common issues: Bugs often come from simple issues like typos, off-by-one errors, or misunderstanding the behavior of a function. Before diving into complex debugging, double-check your assumptions.

3. Version Control: Version control is a tool that helps developers manage changes to their code over time. It allows you to keep track of edits, collaborate with others, and revert to previous versions if something goes wrong.

• Git: Git is the most widely used version control system. It allows you to save snapshots of your code, known as commits, and track the history of your project. It also makes collaboration easier by allowing multiple developers to work on the same project without stepping on each other’s toes.

• GitHub: GitHub is a platform that hosts Git repositories and offers additional tools like issue tracking, project management, and code reviews. As you start collaborating with other developers, GitHub will become an invaluable resource.

• Basic Git commands: Learn basic Git commands like git init, git commit, git push, and git pull. Understanding these commands will allow you to manage your code effectively, both when working solo and with a team.

Helpful Resources for Additional Skills:

How to Build the Right Foundations: Practice, Practice, Practice

Okay, so you’ve got the theory down, but the real magic happens when you put what you’ve learned into action. Mastering data structures and algorithms isn’t just about understanding them it’s about practicing until they feel second nature. Here’s how you can do that:

Start Small: Learn the Basics

Before you dive into big, complex problems, start by getting comfortable with the basics. Things like arrays, stacks, and queues are your best friends.

Example Practice:
Start with problems that help you understand how these data structures work. Try writing a function that reverses a string using a stack. Here’s a quick idea of what that might look like in JavaScript:

function reverseString(inputString) {
    let stack = [];
    
    for (let i = 0; i < inputString.length; i++) {
        stack.push(inputString[i]);
    }

    let reversedString = '';
    
    while (stack.length > 0) {
        reversedString += stack.pop();
    }

    return reversedString;
}

console.log(reverseString("hello"));  

Why this helps: By using a stack to reverse a string, you’re getting a hands-on feel for how stacks work—storing items and then removing them in reverse order. Practice small problems like this daily.

Solve Real Problems: Bring Algorithms to Life

Once you’ve nailed the basics, it’s time to apply what you’ve learned in real-world scenarios. Try using algorithms to solve problems that feel useful in real life.

Example Practice:
Create a simple sorting program to arrange names alphabetically using an algorithm like Bubble Sort or Quick Sort. Here’s a quick example using Bubble Sort:

function bubbleSort(names) {
    let n = names.length;
    for (let i = 0; i < n; i++) {
        for (let j = 0; j < n - i - 1; j++) {
            if (names[j] > names[j + 1]) {
                let temp = names[j];
                names[j] = names[j + 1];
                names[j + 1] = temp;
            }
        }
    }
    return names;
}

let names = ["John", "Emily", "Sarah", "Jake"];
console.log(bubbleSort(names));  

Why this helps: Solving real problems with algorithms deepens your understanding and gives you a tangible result. Whether you’re sorting names or calculating averages, real problems make the learning experience stick.

Write Code Daily: Make It a Habit

The secret to becoming a great programmer is consistency. Choose a programming language (Python, JavaScript, Java, or whatever you like) and make it a habit to write code every day. Even if it’s just for 30 minutes, those 30 minutes add up.

Example Practice:
Pick a small problem every day to practice applying data structures and algorithms. Use platforms like LeetCode or HackerRank for daily challenges that fit your skill level. Here’s an example of a coding challenge you might find on these platforms:

• Problem: Find the maximum number in a list of integers.

    function findMax(nums) {
        let maxNum = nums[0];
        for (let num of nums) {
            if (num > maxNum) {
                maxNum = num;
            }
        }
        return maxNum;
    }
  
    console.log(findMax([1, 3, 7, 0, -5]));  
  

Why this helps: Daily practice is key to internalizing what you’ve learned. It helps you stay sharp and gradually move from simple problems to more complex ones.

Challenge Yourself: Go Beyond Your Comfort Zone

When you feel like you’ve got the basics down, it’s time to level up. Get involved in coding challenges or take on personal projects that push you outside of your comfort zone.

Example Practice:
Join a hackathon or participate in a competitive coding challenge like Google Code Jam or Codeforces. These challenges will push your problem-solving skills to the limit and help you learn new algorithms and techniques.

Why this helps: Challenges force you to think critically and solve problems under time constraints. They help you learn faster and build confidence in your abilities.

Stay Consistent: Build a Routine

Consistency is the key to success in programming (and in most things, really). Set aside time every day or week to practice. Even if you don’t feel like it, just getting in some short coding sessions will make a huge difference in the long run.

Example Practice:
Create a study plan with weekly goals. For example:

• Week 1: Focus on basic data structures (arrays, stacks, queues).

• Week 2: Move on to sorting algorithms (Bubble Sort, Merge Sort).

• Week 3: Dive into more complex algorithms like Binary Search or Dynamic Programming.

A routine ensures that you’re making steady progress. Plus, it makes sure you don’t get stuck on one topic for too long.

Final Thoughts

Programming doesn’t have to be so hard. It’s like building a house: without a strong foundation, everything else feels unstable. But with the right basics like data structures, algorithms, and logical thinking, you’ll be amazed at how quickly you can create great things.

If someone had told me in 2016 that I’d be writing this article today, I wouldn’t have believed them. But with the right preparation, I turned frustration into confidence, and so can you.

Don’t let frustration hold you back. Focus on the fundamentals, practice consistently, and explore the resources I’ve shared. Remember, programming isn’t about being a genius it’s about preparation and persistence. You’ve got this!

If you have any questions, feel free to find me on Twitter at @sprucekhalifa, and don’t forget to follow me for more tips and updates. Happy coding!