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CodeOp Launches Residency Programme to Bridge the Gap Between Bootcamp and First Tech Job

Barcelona, Spain – After +6 years of supporting women, trans and nonbinary individuals in breaking into tech, CodeOp is taking the next step to ensure graduates not only learn but also gain the experience needed to land their first roles in tech. Today, we are excited to announce the launch of the CodeOp Residency Programme, a structured opportunity designed to provide graduates with real-world project experience as they transition from training to employment.

Quality Over Quantity: A New Model for Bootcamps

Unlike traditional coding bootcamps that focus solely on coursework, CodeOp recognises that the real challenge for aspiring tech professionals isn’t just learning to code or model data—it’s getting their foot in the door. Studies show that 93% of hiring managers prefer candidates with hands-on experience, yet entry-level tech roles increasingly require 1-2 years of experience. CodeOp’s Residency Programme is designed to close this gap, offering a 3-month, part-time, remote residency with real partner organisations, allowing graduates to work on real-world projects that strengthen their portfolios and boost their employability.

A Structured, Personalised Pathway to Tech Careers

At CodeOp, we don’t measure success by the number of students we enrol—we measure it by the impact and quality of each graduate’s journey. That’s why we will now only offer seats in our technical courses based on the number of residency seats available each year. This ensures that every graduate who wants to participate can access a high-quality, hands-on experience as part of their bootcamp investment.

Learning by Doing: The Best Career Week is a Real Project

In addition to offering ‘career weeks’ or mock projects, we believe that the best way to ultimately prepare for a tech career in 2025 is by working with a real company on a real project. Our Residency Programme allows participants to collaborate with industry professionals, gain mentorship, and develop critical soft skills like teamwork and communication—all while reinforcing the technical skills they learned in the bootcamp.

First Pilot with FAO: A Proven Model

We’ve already seen this model in action. In our first Residency Programme pilot with the Food and Agriculture Organisation (FAO) at the United Nations, 21 of our Full Stack and Data Science graduates worked as project collaborators, gaining invaluable experience while contributing to meaningful initiatives. This kind of hands-on learning sets CodeOp apart, providing graduates with the practical expertise that hiring managers seek.

Residency Programme: How It Works

The CodeOp Residency Programme is optional but highly encouraged—even for students who are up-skilling for personal growth. Participation includes:

• A 3-month part-time, remote engagement (10 hours/week) with a designated partner organisation
• Real-world experience working on industry projects
• Mentorship and career development support
• An opportunity to enhance portfolios and gain credibility in the job market

A Better Approach to Tech Education

Most bootcamps stop at teaching technical skills, but CodeOp is committed to offering a full start-to-finish experience that takes students from learning to working with a real company. By aligning our course seats with residency availability, we ensure that our students receive the kind of high-touch, personalised experience that leads to real results.

The Residency Programme can be a game-changer for those who want to stand out in a competitive job market. With hands-on project work, guided mentorship, and a direct link to real-world applications, we are redefining what it means to successfully transition into tech.

Applications for the next cohorts are now open. To learn more about the CodeOp Residency Programme and how to apply, visit www.codeop.tech.

If you are a company interested in partnering with CodeOp as a participating organisation in the Residency Programme, please send an email to [email protected].

According to Intuition.com, the number of employees working remotely before the pandemic was 30%, compared to 48% now.

If you find these numbers inspiring, today’s blog will answer all your questions on the digital nomad lifestyle– from whether or not it is the right choice for you to how you can get started.

What defines a Digital Nomad?

In simple words, a digital nomad is a person who leverages technology to work remotely while travelling the world– be it a freelancer, a full-time employee or even an entrepreneur.

Digital nomads come from different backgrounds, but they mostly revolve around tech. When I say tech, I mean some common core tech roles such as software developer, data analyst and cyber security expert. The non-tech roles have great options, too– online teacher, freelance writer, translator, graphic designer, etc.

Pros of being a Digital Nomad

Like any other lifestyle, being a digital nomad comes with its own set of advantages & challenges.

And it’s extremely important to weigh both its pros and cons. To help you make a better choice, let’s have a look at some of them:

1. Flexibility

Probably the most appealing one, the biggest draw of being a digital nomad is the freedom.

The flexibility extends beyond just location. You often have the freedom to set your own work hours so you can work when you’re the most productive.

You get to choose your workspace– to give you an idea, you can work from cafés, some co-working spaces or even a beach (depending on Wi-Fi availability, of course.)

2. Adventure

For many, the opportunity to travel and experience new cultures is the primary appeal of becoming a digital nomad. But it’s not just ‘travel’, you get to live in different parts of the world. And different regions mean learning new languages, trying new cuisines, meeting new people– every day is a new adventure.

When done right, this lifestyle can lead to an enviable work-life balance. For some, moving to a new destination means starting fresh and giving many things a new chance. A part of this is somewhat a con, which we’ll discuss briefly.

3. Financial Perks

One of the biggest perks is earning in a strong currency while living in countries with a lower cost. For example, imagine earning a US salary while living in Thailand or Vietnam. Your money can go much further, and you can enjoy a higher standard of living or save more.

Depending on your home country and how you structure your work, you can take advantage of certain tax benefits. Some countries offer special visas for digital nomads with tax incentives.

Cons of being a Digital Nomad

Yes, there are cons too. Just like everything in life.

1. Isolation

While the digital nomad lifestyle isn’t inherently isolating for everyone—especially for introverts or those who thrive on solitude—it does get lonely for many.

Oftentimes, nomads lose touch with friends and even family back home. Building lasting relationships can be challenging when you’re always on the move. You might miss family gatherings, friends’ weddings, or just the comfort of familiar faces.

Moving to a new place means starting from level zero– you must have the same conversations again. Moreover, working remotely often means less face-to-face interaction with colleagues. Those water cooler conversations and after-work drinks?– they’re harder to come by in the digital nomad world.

Some nomads combat this isolation by staying in co-living spaces or attending networking events, but it’s still challenging for many.

2. Never-Ending Planning

As tempting as the move seems, the reality of digital nomad life usually involves a constant cycle of planning and preparation.

You’re always thinking of new destinations to hit, sorting out the legalities, and finding a place to live in your new country while probably working on an important project for your job.

This perpetual forward-thinking can be exhausting. You’re rarely fully present in your current location because part of your mind is always focused on the next destination.

Questions like “Where will I go next?”, “How long can I stay?” and “Will I be able to work effectively there?” might become a constant backdrop to your daily life.

3. Constantly Moving

Continuous travel and adjusting to new places isn’t as romantic as it seems. One example of its most immediate effects is on sleep quality.

The frequent changes in mattress quality can disrupt your rest pattern. This is similar to the effect that a Time Zone change has on your overall health. Also, each new location will have you searching its transportation systems, service spots, and subway routes, all of which you might eventually need to learn.

The pressure to make the most of each location can also be overwhelming. You might feel guilty if you’re not constantly exploring or experiencing new things, leading to a fear of missing out (FOMO) that can be hard to shake.

A Digital Nomad’s Setup: Essential Gadgets & Equipment

Your ability to work efficiently from anywhere worldwide depends largely on the tools you carry. This would be your utility belt if you were Batman.

And the biggest rule about the utility belt is not to have everything but to find the right balance between what’s needed the most and your overall load. It’s also important to have multi-purpose equipment.

With that in mind, it’s a good idea to regularly assess your load and donate or sell the items that aren’t pulling their weight in your nomadic lifestyle.

Here’s a brief breakdown of the equipment needed to get you started.

1. Laptop

Your laptop will be your mobile office, so choose wisely. Try aiming for a balance between portability & performance. Ultrabooks like the Macbook Air or a Lenovo ThinkPad are popular choices.

A long battery life is another important factor to check for; 8+ hours is a good number. The rest of the specs will also depend on what your role calls for. For example, graphic designers might need a laptop with faster performance than a virtual assistant.

2. Smartphone

This can’t be pushed enough– having a reliable smartphone should be your priority. It is what keeps you connected for most of your journeys. Some digital nomads prefer keeping both their local SIM & their home number running on the same phone.

This calls for a smartphone that offers Dual SIM capability. You might also want a decent camera to capture all the memories and potentially create content. Besides that, a long battery life is also an important factor for phones.

3. Portable Charger (or Powerbank)

Although you’ll always try to keep your devices powered up for long travel days, carrying a power bank or a portable charger for safety would never hurt.

Aim for at least 20,000mAh to charge your laptop and phone multiple times. To support different devices, look for a versatile product with different USB ports– USB-A, USB-C and potentially even AC output. Also, look for models that offer the ‘Quick Charge’ Feature.

4. Universal Power Adapter

This is a common problem that any traveller, nomad or not, might face in a different country. There are many great options– go for one with an all-in-one design.

Although many of these universal power adapters claim to cover over 220 countries, an adapter covering 150 countries would work just fine. Look for one with multiple USB ports & a surge protector– the latter is needed to safeguard your devices from voltage fluctuations.

5. ANC Headphones

A good pair of noise-cancelling headphones is a must for creating a personal workspace practically anywhere. Over-ear typically offers better noise cancellation, while the in-ear ones are more portable. As for battery life, 20+ hours of playback time should suffice. Most remote job roles also need you to connect via online meetings or calls– a good-quality microphone is essential.

Planning your Digital Nomad Journey

1. Selecting your destinations

While personal preferences play a role, there’s much more to consider about a place. Here is a breakdown of some major factors to help you with your decision-making process:

A. Choosing Safe, Women- and LGBTQ-Friendly Locations

While the digital nomad lifestyle offers flexibility and adventure, it’s crucial to prioritize safety, especially when traveling to new and unfamiliar places.

According to Nomad List and Expats in Wonderland, some of the most women and LGBTQ+-friendly locations for digital nomads include Amsterdam (Netherlands), Barcelona (Spain), Toronto (Canada), and Lisbon (Portugal).

Before traveling, research the laws regarding LGBTQ+ rights and women’s safety in your destination. While some countries are LGBTQ+-friendly, others have strict laws or cultural norms that can make travel more challenging.

Many cities with large digital nomad communities host meetups and events for women and LGBTQ+ travelers.

These can be great opportunities to make connections, find safe spaces, and enjoy your journey while feeling part of a supportive community.

B. Cost of Living

This covers a bunch of things. The final cost of living can differ from person to person, depending on their budget & preferences. For example, some enjoy eating out more often than cooking at home. For a clearer picture, take a look at this list:

• Accommodation: Research the area’s average prices for short-term rentals and co-living spaces.
• Food Expenses: Consider both eating out & monthly grocery costs.
• Transportation: Look into public transit options and their costs.
• Entertainment: Factor in costs for activities and socializing.
• Workspaces: If you plan to use coworking spaces, include their membership fees in your budget.

Also, consider how your money might go further in some places than others. Southeast Asia and parts of Eastern Europe are popular for their affordability.

C. Internet Reliability: Check online websites for average internet speeds in different locations & country rankings. Speedtest Global Index & Nomads List are two such sites.

Besides researching the basic availability of fibre optic networks and 4G/5G coverage, look into your possible backup options– this includes the cost of portable Wi-Fi devices or local SIM cards. For a quick look, here is a list of the top 15 countries with the fastest internet speeds, as investigated by Cable.co.uk.

D. Time Zones: If you’re someone with existing clients, consider how the time zone difference will affect your communication. Some nomads prefer to be ahead of their clients’ time zones to get a head start on work, while others prefer to be behind for a more relaxed morning routine. For those working with teams or partners, find a balance that allows for some overlap in working hours.

E. Visa Friendliness: Ease of entry is another important factor– some countries offer visa-free entry or visa-on-arrival for many nationalities. You may also look for countries offering digital nomad visas or other long-stay options. And if you do plan to stay long-term, research the feasibility and legality of visa runs in neighboring countries.

F. Climate and Weather: If you’re not a fan of monsoons or freezing winters, research the region’s climate & plan your destinations accordingly. Be aware of any natural disasters the location is prone to– hurricane seasons, earthquake risks etc. You can also consider whether you’re more productive in warm or cool climates.

Among all this, don’t forget why you’re doing this! Pick places that align with your hobbies. Besides the above factors, having a network of like-minded people can make a huge difference. Some cities have thriving digital nomad scenes with coworking spaces and meetups.

Ultimately, there’s no perfect destination – each place will have pros and cons. The beauty of being a digital nomad is that you can always move on if a place isn’t working out. Start with a shortlist of destinations that tick most of your boxes, and be open to surprises.

2. Visa Options

Nobody wants visa headaches– which is why many nomads try to find places to stay long-term without jumping through too many hoops. To get you started, we have included a short guide on Visa options right below:

A. Tourist Visa

Many digital nomads start their journey using tourist visas, which are typically easier to obtain and usually allow stays ranging from 30 to 90 days, depending on the country.

However, it’s important to note that working on a tourist visa, even remotely for a foreign company, is often technically illegal.

B. Digital Nomad Visa

Several countries have introduced specific visas for remote workers in response to the growing digital nomad trend. Nations like Estonia, Croatia, and Barbados now offer digital nomad visas, allowing stays of 6 months to 2 years. These visas often require proof of income, health insurance, and sometimes background checks.

C. Freelance Visa

For those planning longer stays, some countries like Germany and the Czech Republic offer freelance or self-employment visas. However, these usually involve more paperwork and may require registering a local business entity.

D. Working Holiday Visa

Young travellers (typically under 30 or 35) from specific countries may also consider working holiday visas, which allow work and travel for up to 1-2 years in participating countries. This can be an excellent option for those starting their digital nomad journey.

Now that you’re aware of some common visa options, here is a quick look at some insightful information on the top ten countries by Visa Guide’s Digital Nomad Visa Index.

3. Taxes

Taxes can be a headache even when you’re not globe-trotting. As a nomad, you might need to pay taxes in your home country, the countries you visit, or both. The silver lining in all of this? Many countries have tax treaties to help you avoid paying double taxes.

It’s worth doing some digging to see if these apply to you. But chatting with an international tax expert is often a smart move. It might cost you a bit upfront, but it could save you a ton of hassle (and potentially money).

4. Health Insurance & Precautions

Getting International Health Insurance is crucial for digital nomads. Many countries require proof of health coverage for visa applications, and having comprehensive insurance can protect you from potentially exorbitant medical costs abroad.

Look for plans specifically designed for digital nomads or long-term travellers, which typically offer:

• Coverage in multiple countries
• Telemedicine services
• Emergency evacuation
• Flexibility to adjust coverage as you move

My personal favourites are WorldNomads and SafetyWing.

Vaccinations: Check the CDC or WHO websites for required vaccinations for your destinations. Consider getting common vaccinations like Hepatitis A, Hepatitis B, Typhoid, & Yellow Fever and record your vaccinations (International Certificate of Vaccination or Prophylaxis).

Routine Check-ups: Get a general health check and discuss your travel plans with your doctor. Besides that, get a thorough dental check-up before long-term travel, and if you’re someone with prescription glasses, bring extra contacts or glasses.

First-Aid: Pack common essentials like bandages, antiseptic wipes, pain relievers, and personal medications. Add destination-specific need items like altitude sickness medication or strong insect repellent.

5. Safety Tips

Some key points to keep in mind:

1. When researching your destinations, talk to other nomads about their experiences. Your peace of mind is worth it. Consult government travel advisories and expat forums for current safety information.
2. Stay informed about current events and potential safety issues.
3. Whether staying in hotels or short-term rentals, prioritize properties with good security measures (like 24/7 reception or secure entries.) Also, research the safety of the neighbourhood, especially for late-night returns.
4. Dress modestly and according to local customs to avoid unwanted attention.
5. Be cautious when using public Wi-Fi networks to protect your digital assets.
6. Ensure someone back home has your itinerary and copies of important documents. Add ICE (In Case of Emergency) contacts to your phone’s lock screen.
7. Keep emergency contacts handy. This includes local emergency numbers, your insurance provider’s hotline, and your country’s embassy information.
8. Research safe routes & times & only use well-known taxi companies or ride-sharing apps. If renting a car or scooter, ensure you know local traffic laws and have proper insurance.
9. Stay aware of your surroundings, especially in unfamiliar areas or at night.
10. Consider registering with your home country’s embassy when staying in a foreign country for an extended period. Know the location and contact details of your country’s nearest embassy or consulate.

Long before the first line of code was written, knitters followed step-by-step instructions to create elaborate designs and functional objects. You know what I am talking about if you have crocheted or knitted. It is but a sequence of loops and if-else statements, is it not?

You will be surprised to know that Vint Cerf, one of the “fathers of the Internet,” is known to be a knitter.

These two disciplines, which at first glance couldn’t seem more different, aren’t as far apart regarding the skills involved. You’re probably using the same brain muscles when debugging a code or trying to figure out why your sweater sleeve ended up turned inside out.

Don’t believe me still? Let me prove it.

1. The Basics Elements

Both knitting and coding rely on binary systems at their most basic level. In knitting as well, there are two fundamental stitches: knit and purl. Coding at its most fundamental level is based on 0s and 1s.

Similar to how coding relies on a set of fundamental instructions or “building blocks,” knitting also has its basic elements. In programming, we have variables, functions, and data structures & knitting has basic stitches like knit, purl, and cast on/off.

These basic elements are combined in different patterns to create complex structures in both disciplines. Programmers use loops, conditionals & various functions to build their code. Similarly, knitters deploy different stitches to create different shapes for a piece of garment.

2. Pattern Recognition & Algorithms

One of the most striking similarities between coding and knitting is the use of patterns.

A skilled knitter can look at a complex pattern and break it into repeatable sections. Similarly, in coding, we look for repeating structures to identify opportunities for optimisation or reusable components.

In knitting, a pattern is a set of instructions that, when followed correctly, produces a specific item. This is remarkably similar to an algorithm in programming – a step-by-step procedure for solving a problem or accomplishing a task.

Missing a step or performing an action out of order can lead to errors in the final product (be it a bug in the software or a weird-shaped sweater.)

Yes, I am obsessed with sweaters because I have messed up my fair share while practising.

3. Tools

Knitters have various tools to aid their craft in various ways, similar to how programmers have access to a range of libraries & frameworks.

Suited for different projects, knitting has different needles to choose from, much like different coding frameworks are suited for different types of projects.

Pattern books and stitch dictionaries in knitting are analogous to coding libraries, which offer tried-and-tested solutions that can be incorporated into larger projects.

4. Reuse & Optimisation

A well-known programming principle, “Don’t Repeat Yourself” (D.R.Y.), encourages developers to reduce redundancy for better efficiency and maintainability.

This concept is just as common in knitting, where efficient use of patterns prevents unnecessary repetition. Adhering to this principle in both fields helps establish a cleaner and faster workflow.

Reusable components in coding are like reusable stitch patterns in knitting – they save time and reduce the likelihood of errors.

5. Design Patterns

Design patterns are reusable solutions to common problems that arise during development. This concept is well-established in programming and broadly categorised into creational, structural, and behavioural patterns.

Interestingly, knitting has its own set of design patterns. Specific stitch patterns like cables, lace, or ribbing are used to solve design challenges in knitting projects.

For example, ribbing is often used at the cuffs and waistbands of garments for better elasticity, just as a factory pattern in coding might be used to create objects without specifying their exact class.

6. Debugging

When things go wrong in either of these disciplines, the first step is to track back through your work & look for the mistake. Ever spent hours hunting down a missing semicolon in your code (or indentation if you’re a PyUser?

We do the same thing in knitting before we realise a forgotten stitch three rows back. This is troubleshooting, a process for which a coder goes through their program to find & fix the “bugs”.

In knitting, this is often called “frogging” – ripping out rows of stitches to fix a mistake. These processes require a good eye for detail and patience to identify where the error occurred.

7. Automation

The evolution of both knitting and coding has seen the introduction of tools that automate repetitive tasks.

In this age, machines & looms can now produce complex patterns at high speeds, similar to how Integrated Development Environments (IDEs) in coding automate many aspects of the programming process.

Computer-aided knitting produces intricate designs that would be time-consuming or impossible to produce by hand. This mirrors how modern coding tools can generate boilerplate code or suggest completions to help you focus on more complex aspects of the project.

8. Knitting Patterns vs. Programming Languages

Knitting patterns can be viewed as a form of programming language. Each has syntax, symbols, and logic that must be followed to achieve the desired outcome.

Different knitting techniques, such as Fair Isle or intarsia, could be likened to different programming paradigms like object-oriented or functional programming.

Just as a programmer must be fluent in the language they’re using, a knitter must be able to read and interpret knitting patterns accurately to create the intended design.

9. Continuous Learning

If you’re the type who likes to kick back and coast on what you already know, you’re unlikely to grow fond of these disciplines. Both fields are like that friend who’s always dragging you to try new things.

That said, continuous learning here is not just beneficial but necessary. Technology evolves rapidly, so one must constantly update their skills and learn new languages or frameworks.

Similarly, knitters are always learning new techniques & exploring new tools or yarns.

Frequently Asked Questions (FAQs)

1. Can learning to knit actually help improve my coding skills?

Learning to knit is unlikely to directly impact your coding skills lest you need a distraction and a hobby to cool off. Knitting teaches you pattern recognition, attention to detail & problem-solving abilities – all of which are great for a coder.

If you know how to knit, many of your skills will be directly transferred once you start your coding journey. However, if you want to start coding and don’t know how to knit, start by learning coding instead of vice versa.

2. Are there any programming languages specifically designed for knitting?

While not a traditional programming language, there are notation systems for knitting patterns that resemble code.

Additionally, some machines use KnitScript and similar languages. There are also projects aimed at creating programming languages for textile design.

3. How can I combine my interests in both coding and knitting?

There are several interesting ways to combine these interests. You can explore digital knitting machines, create knitting pattern generators, or develop apps for knitters.

Some knitters incorporate electronics into their projects to create interactive textiles. You could also contribute to open-source knitting-related software or create visualisation tools for knitting patterns.

Localhost is your machine’s web server during development. It allows you to test websites and applications in a safe, controlled environment.

In lay terms, the combination of localhost and ports (like 8080) enables communication between your system and the web browser during testing.

Let’s properly understand localhost.

Simply put, localhost is your computer’s way of talking to itself. In networking terms, it refers to your machine acting as a server, allowing you to run applications locally rather than on a remote machine (server).

The IP address typically used for localhost is 127.0.0.1, which we call a loopback address.

When you run a web server on your machine (using technologies like Node.js, Apache, or Tomcat), your computer listens for incoming traffic directed to localhost. This allows developers to simulate how their applications will run on the web without needing an actual public-facing server.

If you’re a web developer and want to test the website or app you’re building, you don’t have to put it live on the internet right away. Instead, you can “host” it locally on your computer, making it accessible only to you using localhost.

There are three big reasons why every programmer insists on using localhost:

• It’s a safe environment to run and test code without exposing it to the public.
• There’s no need for network delays when accessing your local machine. It’s instant.
• Your work stays on your machine until you’re ready to deploy.

For example, when you type http://localhost in your browser’s address bar, your machine checks if a web server is running locally. If there is, it serves the files from your local machine just like a real web server would on the internet.

What is Port 8080?

In networking, ports are communication endpoints that allow devices to differentiate between various services or applications running on the same machine.

A computer can run multiple programs that need network access, so ports help direct the incoming and outgoing data to the correct service.

For example, I have a home server with a static IP address (192.168.1.25). I have about a dozen apps on this server, so I use ports to access them.

Here’s how it looks:

• Emby Media Player: 192.168.1.25:8096
• SABnzbd Downloader: 192.168.1.25:8010
• Portainer (for docker): 192.168.1.25: 8000
• Uptime Kuma: 192.168.1.25:8100

…and many others.

Port 8080 is one of the many ports a web server can use to listen to incoming requests. While port 80 is typically the default port for HTTP traffic (the same protocol that powers the web), 8080 is commonly used as an alternative, especially for development and testing environments.

Why 8080?

Port 80 is often already used by other services (like a production web server), so developers commonly use 8080 for testing without conflict.

Additionally, the number 8080 is easy to remember and is frequently used in documentation and examples for local development.

How to Access Localhost on Port 8080?

To access localhost on port 8080, you’ll first need a web server or application running locally and listening on this port.

Here’s a step-by-step guide to try and learn through practice:

Step 1: Start a Local Web Server

Starting a web server will differ depending on the programming language or framework you’re using. Here are a few common examples:

Node.js:

const http = require('http');

const server = http.createServer((req, res) => {

res.statusCode = 200;

res.setHeader('Content-Type', 'text/plain');

res.end('Hello Worldn');

});

server.listen(8080, '127.0.0.1', () => {

console.log('Server running at http://127.0.0.1:8080/');

});

Python: If you have Python installed, you can easily start a server in your current directory:

python3 -m http.server 8080

Apache/Tomcat: Many web servers like Apache or Tomcat are pre-configured to use port 8080 for testing purposes. Simply start the server, and it will listen on port 8080.

Step 2: Open Your Browser

Once the server runs, open a browser (like Chrome, Firefox, or Edge) and type http://localhost:8080 into the address bar. This URL tells your browser to connect to your local machine (localhost) using port 8080.

Step 3: View Your Application

You should see your web application or server response if everything is set up correctly. For instance, in the Node.js example above, your browser will display “Hello World” when visiting http://localhost:8080.

Here are some troubleshooting tips if something goes wrong:

• Server not running: If you get a “connection refused” or similar error, ensure your server is running and listening on port 8080.
• Firewall issues: Some firewall settings may block communication on certain ports. Make sure your firewall allows traffic on port 8080 for local connections.
• Port conflicts: Ensure that port 8080 is not already used by another service on your machine. If so, consider using another port (e.g., 3000, 5000, etc.).

Securing Localhost on Port 8080

Although localhost is typically considered safe because it’s restricted to your machine, there are some best practices to ensure that your local server is secure. This could be important if you intend to expose it to external networks.

1. Use HTTPS

While localhost doesn’t require HTTPS by default, using it can add an extra layer of security, especially when working with sensitive data. You can easily set up a local HTTPS server by generating a self-signed SSL certificate.

For example, in Node.js, you can use the https module:

const https = require('https');

const fs = require('fs');

const options = {

key: fs.readFileSync('key.pem'),

cert: fs.readFileSync('cert.pem')

};

https.createServer(options, (req, res) => {

res.writeHead(200);

res.end('Secure connection established');

}).listen(8080, '127.0.0.1', () => {

console.log('Server running at https://localhost:8080/');

});

This ensures that your local development environment mimics the security of a production server.

2. Configure Firewalls

Ensure that port 8080 is only accessible from your machine (localhost) and not from external devices unless necessary. You can do this by setting your firewall to block all external requests.

• Windows: Go to “Windows Defender Firewall” > “Advanced Settings” and configure rules to restrict access to port 8080.
• Mac/Linux: Use firewall tools like ufw or iptables to manage access on port 8080.

3. Limit Exposure with VPN or SSH Tunnels

If you need to expose your localhost server to external networks (for example, to show your work to a client or colleague), consider using a VPN or SSH tunnel.

My favourite tool for this is using Cloudflare’s tunnels through Cloudflare One. It is basically a network-as-a-service (NaaS) solution to establish secure remote connections.

These methods provide a secure way of sharing your local server without exposing it directly to the internet.

4. Authentication and Access Control

If you are working on more complex projects, consider adding basic authentication or token-based access controls to ensure that only authorised users can access your local application. This is especially important when exposing APIs or sensitive data.

So, let’s use this week to clear some of the most common doubts regarding the best practices in HTML and CSS. Today, we’ll talk about the two common, sometimes interchangeable, HTML elements: ‘div’ and ‘section’

In modern web development, writing clean, semantic HTML code is not just a best practice—it’s essential for accessibility, SEO, and maintainability.

Trust me, I had to deal with this when we first started developing codeop.tech. One of the devs we hired didn’t use the two elements properly, which made me think that maybe nobody is asking this question in their learning phase.

In lay terms, ‘div’ is a generic container that groups elements together, and ‘section’ is a semantic tag that defines content sections.

Let me elaborate.

Understanding the ‘div’ Element

The ‘div’ element is one of the most commonly used HTML tags. It stands for “division” and is primarily used as a container to group other elements together.

However, ‘div’ is non-semantic, meaning it doesn’t provide specific meaning to the content it wraps. Remember this because it’s a major difference.

It’s typically used when no specific element is available, and its primary purpose is layout and styling.

Let’s use an example. Say we need to make a small marketing block with text, images and a background to be used within landing pages.

Using a ‘div’ here helps us keep all the components together for styling and layout without suggesting that they represent distinct sections of a page like a ‘section’ would.

<html>

<head>

<title>Marketing Block Example</title>

<style>

body {

font-family: Arial, sans-serif;

margin: 0;

padding: 0;

background-color: #f0f0f0;

}

.marketing-block {

width: 80%;

margin: 40px auto;

padding: 20px;

background-color: white;

border-radius: 8px;

box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);

text-align: center;

}

.marketing-block img {

width: 100%;

max-width: 400px;

height: auto;

border-radius: 8px;

}

.marketing-block h2 {

font-size: 2rem;

color: #333;

margin: 20px 0;

}

.marketing-block p {

font-size: 1rem;

color: #666;

margin-bottom: 20px;

}

.cta-button {

background-color: #28a745;

color: white;

padding: 12px 20px;

text-decoration: none;

border-radius: 5px;

font-size: 1rem;

}

.cta-button:hover {

background-color: #218838;

}

</style>

</head>

<body>

<div class="marketing-block">

<img src="https://via.placeholder.com/400x300" alt="Product Image">

<h2>Introducing Our New Product</h2>

<p>Experience the next level of innovation with our new product. Designed to bring you the ultimate efficiency and comfort in your daily life.</p>

<a href="#" class="cta-button">Learn More</a>

</div>

</body>

</html>

When to Use ‘div’:

Use ‘div’ elements when you need a generic container for styling or layout purposes without intending to define a specific section of your document’s content.

It’s also great when used with CSS frameworks like Flexbox and Grid, where structural elements are important, but the semantics aren’t.

Understanding the ‘section’ Element

Unlike ‘div’, the ‘section’ element is semantic. It defines a section of a document and usually includes a heading (<h1> to <h6>) to indicate what that section is about.

The ‘section’ tag is meant to group related content under a common theme, such as articles, chapters, or a report section.

We use section> to improve the readability of your code and help search engines understand the content better.

<!DOCTYPE html>

<html lang="en">

<head>

<title>Understanding </title>

<style>

.section-style {

margin: 20px 0;

padding: 10px;

background-color: #e0f7fa;

}

</style>

</head>

<body>

<section class="section-style">

<h1>About Us</h1>

<p>We are a team of developers passionate about web development.</p>

</section>

<section class="section-style">

<h2>Our Mission</h2>

<p>Our mission is to build user-friendly web applications.</p>

</section>

</body>

</html>

When to Use ‘section’:

• Use it when your content logically belongs together and can be grouped under a common heading.
• Ideal for long-form content like articles, reports, or documentation, where you want to divide the page into meaningful sections.
• It improves accessibility by clearly indicating content blocks to screen readers and helps with SEO by giving semantic context to the document’s structure.

When to Use ‘section’ Over ‘div’

The ‘section’ element should be used when grouping content that forms a logical, standalone section of your webpage.

1. Systematic Grouping: When the content is related by a common theme and can be independently summarized. For example, a section of a webpage that talks about a company’s services, blog posts, or testimonials.
2. Logical Structure: If the content could stand alone as a separate part of the document and would make sense as a part of the site’s navigation or outline, it’s a good candidate for a ‘section’.
3. Content Sections with Headings: Typically, you’ll see ‘section’ elements containing headings like <h2>, <h3>, etc. For example, in an article, each section could start with a heading to define the content.
4. Accessibility & SEO: Search engines and screen readers use the structure provided by ‘section’ to better understand the content and its meaning.

When to Use ‘div’ Over ‘section’

The ‘div’ element is a more general container that groups elements for styling purposes without implying any specific meaning or structure.

1. Styling and Layout: When applying specific styles (e.g., padding, margins, background color) to a group of elements. This is especially useful for applying classes or IDs for styling purposes.
2. Interactive Elements: If you’re grouping buttons, images, or content that will be styled and animated , ‘div’ is a great choice.
3. Multiple Components: When you have content that doesn’t need a heading or isn’t part of a broader section, ‘div’ helps group elements without adding extra semantic weight.

Using ‘section’ and ‘div’ Together

In this example, we create a small webpage with a section about services and a testimonial section, each containing individual divs for layout purposes.

<!DOCTYPE html>

<html lang="en">

<body>

<div class="container">

<!-- Services Section -->

'section'

<h2 class="section-title">Our Services</h2>

<div class="service">

<div class="service-icon"> </div>

<div class="service-description">

<h3>Web Development</h3>

<p>We build fast, responsive websites tailored to your business needs using the latest technologies.</p>

</div>

</div>

<div class="service">

<div class="service-icon"> </div>

<div class="service-description">

<h3>Data Analytics</h3>

<p>We provide insightful data analysis to help businesses make data-driven decisions.</p>

</div>

</div>

</section>

<!-- Testimonials Section -->

'section'

<h2 class="section-title">Client Testimonials</h2>

<div class="testimonial">

<div class="testimonial-author">John Doe, CEO of TechCorp</div>

<p> "The web development services exceeded our expectations. Our site is faster, more responsive, and we've seen an increase in user engagement!" </p>

</div>

<div class="testimonial">

<div class="testimonial-author">Jane Smith, Marketing Director</div>

<p> "Their data analytics solutions helped us streamline our marketing campaigns and increase our ROI by 20%!" </p>

</div>

</section>

</div>

</body>

</html>

“Why can’t you just use px (pixels)? Isn’t that what matters in the end, no?”

I think it’s a valid question but an incorrect outlook. Using em and rem leads to a more responsive and interactive end-product, and they’re easier than using px for a big codebase once you understand the use case properly.

1. What are CSS Units?

Let’s go back a few steps and understand the fundamentals first.

In lay terms, CSS units define how elements are sized and spaced in a layout. Broadly speaking, these units fall into two categories: absolute units and relative units.

Absolute Units: These include px (pixels), cm (centimeters), mm (millimeters), and (inches). For example, 100px will always be 100 pixels on a small mobile screen or a large desktop monitor. While absolute units are predictable, they are less ideal for responsive design.

Relative Units: These units scale based on other values, with em and rem used most. Relative units are ideal for responsive and accessible designs since they can be adapted across different devices and screen sizes.

2. What is Em, and how to use it in CSS?

The em unit is a relative unit that scales based on the size of its parent element. So, any change in parent size will be accordingly reflected in the child elements as well.

It’s highly useful when you want your elements to remain scalable and flexible as the environment around them shifts.

Let’s break it down with an example:

<div class="parent" style="font-size: 16px;">

<p class="child" style="font-size: 2em;">This text will be 32px</p>

</div>

In this example:

• The parent div has a font size of 16px.
• The child p element uses 2em, meaning its font size will be 2 times the parent’s (16px * 2 = 32px).

Note: Because em is a multiplier, it cascades down through your CSS. This can sometimes cause unintended issues when nesting elements.

For example, if you have multiple nested elements, the font size could keep multiplying, leading to unexpected, oversized elements.

<div class="parent" style="font-size: 16px;">

<div class="nested-parent" style="font-size: 1.5em;">

<p class="child" style="font-size: 1.5em;">This text might become too large!</p>

</div>

</div>

Here’s the math:

• The nested parent has a font size of 1.5em, meaning 1.5 * 16px = 24px.
• The child inside the nested parent has a font size of 1.5em, meaning 1.5 * 24px = 36px.

Effective Use of em:

This CSS unit is great for scalable layouts where you want to maintain flexible sizing within a specific module or component of your design.

It works great, provided you know the cascading effect and don’t use it in (complicated) nested elements. Em is not ideal for globally consistent sizing, as it depends heavily on parent elements.

3. What is Em, and how to use it in CSS?

The rem unit, short for root em, is also relative, but instead of the parent, it’s calculated based on the root element’s font size — usually the <html> element.

Let’s look at an example:

<html style="font-size: 16px;">

<div class="container">

<p class="text" style="font-size: 2rem;">This text will be 32px</p>

</div>

</html>

In this case:

• The root <html> element has a font size of 16px.
• The p element uses 2rem, meaning its font size will always be 32px, regardless of the font size of any parent elements.

Unlike em, rem avoids the compounding issue. It stays consistent across the entire page, so it’s widely preferred for global sizing systems like padding, margins, and typography.

Pro Tip: If the root element <html> doesn’t have a pixel size defined, rem will default to whatever the browser (client-side) has as default. And this is usually 16px for most browsers and devices.

4. How do you choose between em and rem?

Choosing between em and rem largely depends on the context of your design and the output you want to achieve.

Use Rem for Consistent, Global Sizing:

Here’s a stylesheet example:

html {

font-size: 16px;

}

h1 {

font-size: 2rem; /* Always 32px, regardless of nesting */

}

p {

margin-bottom: 1rem; /* Always 16px */

}

Here, both the heading and paragraph margins scale based on the root font-size. If the user changes their default font size in the browser, all elements using rem will scale accordingly.

Use Em for Component-Specific Scaling:

Em is useful when you want elements to scale relative to their immediate parent, like modular components or nested elements.

This is great for self-contained components that must be flexible within their context.

.button {

font-size: 1.2em; /* Relative to the parent font size */

padding: 0.5em 1em; /* Padding scales with font size */

}

.large-button {

font-size: 1.5em; /* Larger buttons inherit scalable padding */

}

In this example, the padding for buttons is determined based on the button’s font size. When the large button gets a bigger font size, its padding scales automatically.

Combine Rem for Layout and Em for Components:

For global layouts and typography, use rem to maintain a consistent scale. Use em for elements that need to adapt to parent-specific styles, like buttons, menus, or cards.

html {

font-size: 16px;

}

.container {

padding: 2rem; /* Consistent padding regardless of nesting */

}

.card-title {

font-size: 1.5em; /* Scales based on parent size */

}

.card-text {

font-size: 1em; /* Matches parent size for consistency */

}

The container uses rem for consistent padding across the site, while the card’s text uses em, allowing the content within the card to scale based on the parent font size.

5. Can I mix rem, em, and px in the same stylesheet?

Yes, you can mix rem, em, and px in the same stylesheet, but it’s important to do so thoughtfully and for specific reasons.

To create an accessible, responsive, scalable and (most importantly) effective stylesheet, you should combine rem, em and px properly. Remember their strengths.

Rem is great for global sizing, em is ideal for component-specific sizing such as padding and margins on specific elements that should respond to the size of text. And px should be used for precision on elements that shouldn’t respond to screen or size changes.

For example, use rem for layout properties, em for component-level adjustments, and px for precise elements like borders and icon sizes.

/* Global settings */

html {

font-size: 16px; /* Base font size for rem */

}

body {

font-family: Arial, sans-serif;

margin: 0;

padding: 0;

}

/* REM for Layout and Typography */

.site-header {

background-color: #333;

color: white;

padding: 2rem; /* Spacing based on root font size */

text-align: center;

}

.logo {

font-size: 2rem; /* Header logo scales with root font-size */

margin: 0;

}

.main-nav ul {

list-style-type: none;

padding: 0;

}

.main-nav li {

display: inline-block;

margin-right: 1rem;

}

.main-nav a {

color: white;

text-decoration: none;

font-size: 1rem; /* Consistent font-size using rem */

}

/* EM for Component-Based Scaling */

.cta-button {

font-size: 1.2em; /* Scales based on button's font size */

padding: 0.5em 1em;

background-color: #007bff;

color: white;

border: 2px solid #007bff; /* Border in px */

border-radius: 5px; /* Exact size in px */

}

.cta-button:hover {

background-color: white;

color: #007bff;

}

/* Mixing REM, EM, and PX in Components */

.hero {

text-align: center;

padding: 4rem 1rem; /* REM for consistent layout spacing */

}

.hero h2 {

font-size: 2.5rem;

margin-bottom: 1.5rem;

}

.features ul {

list-style-type: none;

padding-left: 2rem;

}

.features li {

font-size: 1.2em; /* EM for component-specific scaling */

margin-bottom: 0.5rem;

}

/* Footer uses rem for typography, px for specific sizing */

.site-footer {

background-color: #f4f4f4;

padding: 1.5rem 0;

text-align: center;

border-top: 1px solid #ddd; /* Pixel-perfect border */

}

.site-footer p {

font-size: 1rem; /* Scaled with rem */

margin: 0;

}

Here’s the HTML page:

<!DOCTYPE html>

<html lang="en">

<head>

<meta charset="UTF-8">

<meta name="viewport" content="width=device-width, initial-scale=1.0">

<title>Mixing rem, em, and px</title>

<link rel="stylesheet" href="styles.css">

</head>

<body>

<header class="site-header">

<h1 class="logo">My Website</h1>

<nav class="main-nav">

<ul>

<li><a href="#">Home</a></li>

<li><a href="#">About</a></li>

<li><a href="#">Services</a></li>

<li><a href="#">Contact</a></li>

</ul>

</nav>

</header>

<main class="content">

<section class="hero">

<h2>Welcome to My Website</h2>

<p>We are happy to provide you with the best services in the industry.</p>

<button class="cta-button">Learn More</button>

</section>

<section class="features">

<h3>Our Features</h3>

<ul>

<li>High Quality</li>

<li>Expert Support</li>

<li>Affordable Pricing</li>

</ul>

</section>

</main>

<footer class="site-footer">

<p>© 2024 My Website. All Rights Reserved.</p>

</footer>

</body>

</html>

Explanation of Mixing rem, em, and px:

The layout of the site (headers, body, and spacing) is controlled using rem. This ensures consistency across the site. If the root font size (html { font-size: 16px; }) changes, all rem-based values scale proportionally.

The .cta-button uses em for font size and padding. This allows the button to scale based on its context. If the parent element’s font size changes, the button scales with it.

Similarly, the .features section uses em for list items (li), allowing each list item to scale based on the section’s font size.

Specific elements like borders (2px solid #007bff for buttons and 1px solid #ddd for the footer) use px for pixel-perfect sizing.

By understanding the fundamentals of coding, you’ll be better equipped to learn and master any programming language.

Firstly, get clear on why you want to learn how to code. Then, dive into the foundational coding concepts, like variables, operators, and data structures. Next, choose the programming language you would like to start with.

You can use online courses, bootcamps, or formal education to advance your knowledge, but practise often and build projects. This will help you get more comfortable with coding.

Getting Started with Coding

1. Choose Your First Programming Language

The first step in your journey is choosing a programming language. Your choice will depend on your goals, such as the projects you want to work on.

Are you interested in web development, mobile apps, or data science? Each field has its go-to languages:

• Python: Ideal for beginners, Python is one of the most popular languages due to its simplicity and versatility. Whether you’re interested in web development, data science, automation, or artificial intelligence (AI), Python has you covered.
• JavaScript: Essential for web development, JavaScript allows you to create interactive websites and apps. It works for both front and backend development, making it a strong choice for web or mobile app development.
• Ruby: Known for its elegant syntax, Ruby is another beginner-friendly language. It’s particularly strong for building web applications, especially with the Ruby on Rails framework.
• Java: If you’re considering mobile development, especially for Android, Java is a solid choice. It’s also widely used in enterprise-level applications.

Pro Tip: If you’re unsure, start with Python. It’s easy to learn and versatile, with a large support community. Once you’ve mastered the basics, you can easily switch to other languages.

2. Set Up Your Development Environment

Here’s a quick guide to setting up:

Text Editors vs Integrated Development Environments (IDEs):

Text editors like Visual Studio Code (VS Code) are lightweight and easily allow you to write code in various languages.

IDEs like PyCharm (for Python) or IntelliJ IDEA (for Java) offer additional features like debugging and code completion, making them great for more advanced coding tasks.

Version Control: You’ll need to get used to saving and tracking changes to your code, as this is essential to working on projects of any size. Git is a popular version control software used by over 95% of developers.

GitHub is a code storage platform built upon Git and works seamlessly. Git is also essential to working on projects with many people or across computers, making tracking changes easier.

It’s so important that our former teaching assistant, Anna Skoulikari, wrote a book about it! Check out ‘Learning Git‘ to see how you can get started on this essential software. Anna has also designed online courses for Git on Udemy, and a step-by-step guide on freeCodeCamp.

You can quickly get started by installing Git and creating a GitHub account. Practice pushing and pulling code changes from your local machine to GitHub.

Pro Tip: GitHub also acts as a portfolio where you can showcase your projects to potential employers.

Basic Programming Concepts

1. Syntax and Structure

Programming languages may look different, but they share common structural elements. Understanding basic syntax is like learning the grammar of a new language.

Variables: Variables are placeholders for data. In Python, you can create a variable without declaring its type, like so: my_variable = 5.

In contrast, languages like Java require you to define the type of data: int my_variable = 5;

Data Types: Most languages have basic data types, such as:

• Integers: Whole numbers like 5 or -3
• Strings: Text, like “Hello, World!”
• Booleans: True or false values (True, False)

Functions: Functions allow you to encapsulate blocks of code that can be reused. In Python, you define a function using the def keyword:

def greet():

 print("Hello, World!")

greet()  # Calls the function and outputs "Hello, World!"

2. Control Flow

Control flow statements guide the direction in which the program executes.

Conditionals (if/else): Conditionals allow your program to make decisions based on certain conditions. For instance, you can have your code check if a number is positive or negative:

x = 10

if x > 0:

 print("Positive")

else:

 print("Negative")

Loops (for/while): Loops enable you to repeat a code block multiple times. A for loop can iterate over a range of numbers or items in a list:

for i in range(5):

 print(i)  # Prints 0, 1, 2, 3, 4

count = 0

# A while loop runs as long as a condition is true:

while count < 5:

 print(count)

 count += 1

3. Data Structures

Data structures let you store data efficiently.

Lists/Arrays: Lists (or arrays) store a sequence of values. In Python, you can create a list like this:

fruits = ["apple", "banana", "cherry"]

print(fruits[0])  # Outputs: apple

You can add, remove, or modify items in a list with various methods.

Dictionaries/Objects: Dictionaries (or objects) store key-value pairs, which makes them great for representing real-world data:

student = {"name": "Alice", "age": 25, "course": "Data Science"}

print(student["name"])  # Outputs: Alice

Knowing how to use these data structures will help you tackle complex coding tasks, which are foundational in storing and manipulating data.

Writing Your First Program

The first program most beginners write in any language is the classic “Hello, World!” It’s a simple exercise that familiarises you with the basic syntax of your language.

Let’s go over how to write this in Python:

print("Hello, World!")

That’s it! Running this in your Python environment will output Hello, World! to the screen. Here’s how to break it down:

• print(): This function outputs text or data to the screen.
• “Hello, World!”: The text you want to display goes inside quotation marks, making it a string.

Once you’ve mastered the basics, like printing text, you can move on to more complex tasks. Try modifying the program to take user input:

name = input("What's your name? ")

print(f"Hello, {name}!")

In this case:

• input(): Asks the user for input.
• F-string: A formatting method in Python that allows you to insert variables directly into strings.

This simple progression from displaying text to interacting with the user is an excellent way to understand how programs work in real life.

Best Practices for Beginners

1. Write Clear and Descriptive Code

Good code is self-explanatory. Use variable names that describe the data’s representation and function names that explain what they do.

Bad Example:

x = 5

y = x * 2

Good Example:

radius = 5

diameter = radius * 2

By using meaningful names, you or anyone looking at your code can quickly understand what’s going on without dissecting it line by line.

2. Comment Your Code

Comments are notes we (developers) write to explain what certain parts of the code do. It’s a habit that will help you in complex projects, especially when you revisit your code after a while. Or when working with different teams.

This function takes a user’s name and prints a greeting

def greet_user(name):

 print("Hello, {name}")

Use comments to describe the “why” behind your logic, not just what it does—especially when dealing with complex algorithms.

3. Avoid Hard-Coding Values

Hard coding means putting fixed values into your program instead of making it flexible and reusable. For instance:

Bad Example:

total_price = 100 * 2  # Only works for this case

Good Example:

price_per_item = 100

quantity = 2

total_price = price_per_item * quantity  # Works for any case

Always aim to write reusable code that can be easily adjusted for different scenarios.

Alternatively, if there are constant values, you should hard code them using a constant variable.

Example:

SKU_PRICE = 100

How long does it take to learn coding from scratch?

Most programmers will say it takes three to six months to be fully comfortable with the basics of coding, but this depends entirely on the person and their learning pace. However, no programmer knows everything.

Coding, by nature, involves many ever-evolving concepts and new developments, so you can never stop learning in this position, even as a professional.

Developing Good Coding Habits

Developing strong habits early in your coding journey will save you headaches later and accelerate your growth as a developer.

1. Practise! Practise! Practise!

Coding is like any other skill—it requires regular practice. Aim to set aside time every day, even if it’s just 30 minutes, to write and experiment with code.

The more you practise, the better you will become at writing code and solving problems. This consistency will help you reinforce the concepts you’ve learned and build your coding skills.

2. Break Down Problems

Before jumping straight into coding, break down the problem into smaller, manageable parts.

This approach is often called “divide and conquer” and is essential when working on larger projects. Write pseudocode or outline your logic in plain English before you start coding.

For example, instead of diving into code for a complex sorting algorithm, first outline what each step will look like:

• Get the list of numbers
• Compare each number with the next
• Swap their positions if needed
• Repeat until the list is sorted

Breaking down problems helps you think more logically and systematically, which is a valuable skill in coding.

3. Review and Refactor Your Code

Once you’ve written your code, take some time to review it. Can it be written more efficiently? Are there sections where you’re repeating yourself?

Refactoring is improving your code’s structure without changing its behaviour. For example, if multiple lines do the same thing, you can refactor it into a loop or function to simplify it.

4. Learn to Debug Efficiently

Debugging is an inevitable part of coding, and learning how to do it efficiently will save you hours of frustration. When your program doesn’t behave as expected:

• Use print() statements to see what’s happening with your variables.
• Utilise debugging tools available in your IDE, such as breakpoints, which allow you to step through your code line by line.
• Read error messages carefully—they often point you directly to the problem.

Developing these habits will improve your efficiency and make you a better, more thoughtful programmer.

5. Coding Challenges

Many online platforms and coding challenges are available that provide practice opportunities. These platforms often have coding exercises and challenges that you can work on to improve your skills.

CodeWars features varying levels of coding exercises available in multiple programming languages. The challenges are free to solve multiple times, and you can access others’ solutions as soon as you’ve figured them out.

HackerRank is another great platform for coding challenges. It also has varying levels and languages to work in. Both sites are often used in professional interviews, so they are great tools to practise your problem-solving skills.

This shift is especially empowering for women, trans, and nonbinary individuals, who often face barriers in traditional education environments.

At CodeOp, we’ve seen firsthand how diverse voices can thrive in tech, regardless of background or previous experience. The tech industry increasingly recognises that talent comes in many forms, and with the right approach, anyone can carve out a successful career.

After running CodeOp for some time, I have become more sure than ever that it’s never too late to start. Especially now that the opportunities are more accessible than ever.

You don’t need a degree to break into the tech industry. With the right skills, determination, and a strategic approach, you can find opportunities and build a successful career in tech.

Step 1: Start studying immediately.

Countless websites, platforms, and courses can teach you valuable tech skills and knowledge. Additionally, free or low-cost options like Udemy courses and part-time bootcamps are often available, making it accessible for those on a tight budget.

1. Bootcamps

According to research by Indeed, 72% of employers think bootcamp graduates are just as prepared and likely to be high performers as candidates with computer science degrees.

Another 12% think bootcamp graduates are more prepared and likely to succeed than traditional job candidates.

Here are some pros and cons to help you make an educated decision:

Pros: Bootcamps surpass formal education in flexibility and affordability. Most can be as short as a few weeks and offer part-time, remote options.

In addition, they are also taught by industry professionals and provide updated education related to in-demand skills and technologies. This allows for a greater demographic to access that transition to a new tech career.

Cons: Bootcamps can move faster than other learning programs, making the learning curve more intense. However, if you stay consistent and compassionate towards yourself, you can succeed.

Investing in an online bootcamp like CodeOp allows you to learn the latest industry-relevant skills, work on real-world projects, and access dedicated career support to guide you from learning to landing a job.

2. Online Courses

Another great way to learn tech-related skills without a degree is to take advantage of online learning resources. Websites like Coursera, Udemy, and Codecademy offer a wide range of courses in programming, web development, data science, and more.

Most of these courses are self-paced, which might be what you need if you have other time-consuming obligations.

Pros: There are many tech resources available online, with some being free. They are also often put together by industry professionals, depending on the course provider. You also have the freedom to choose when you want to learn, and some even give certificates upon completion.

Cons: Mentorship and one-on-one support are not always available, and this can be extremely helpful as a beginner. Developing best practices, and working on a project with a team can be harder to accomplish.

3. Self Study

Nowadays, you can find content enabling you to teach yourself tech skills in all corners of the internet. YouTube has beginner-friendly resources for just about any tech-related skill, as well as in-depth explanations of concepts and tutorials for projects.

Pros: With self study, you are free to study what you want at your own pace. You are in complete control of how much content you take in at any given time, and how you choose to practise.

Cons: While you may be learning from real people, the experience is not personalised nor intimate, so you are not always likely to have all your questions answered. The concern of best practices is also raised here, as learning in this case would be done without oversight.

One way to bypass that would be using AI models like ChatGPT, Claude or Perplexity. One of these LLMs could act as your “teacher,” and make sure you don’t stray in the wrong direction.

However, that’s not a foolproof solution given how often these models hallucinate.

Step 2: Focus on Practical Projects

While theory is essential, our industry values practical experience even more. Employers want to see that you can build, debug, and deploy real-world applications.

1. Personal Portfolio

Your portfolio will become one of the most important assets in your job search. According to a survey by a college in Hong Kong, 90% of employers prioritize practical experience over academic credentials when evaluating candidates.**

A good portfolio should include diverse you’re that demonstrate your versatility.

Start by identifying projects that align with your interests and the skills you want to showcase. This could be creating a website, developing a mobile app, or contributing to open-source projects with other professionals.

When building projects, focus on solving real-world problems, as this simulates your work in a professional setting.

A great example of this is one of our Full Stack Development students, Zarina, who developed the website “CycleSavvy” as her very first project.

Zarina’s site helps people with periods track their cycle and provides them with self-care tips related to the symptoms they may feel on any given day. It also provides their partners with tips on supporting them through such times.

3. Internships and Apprenticeships

According to a Glassdoor report, interns in software engineering roles can earn an average of £47,002 per year in London, making it a financially viable way to gain experience while learning.

In addition to personal projects, consider internships and apprenticeships. Many tech companies offer paid internships or apprenticeships for non-degree holders, providing hands-on experience while learning from seasoned professionals.

Step 3: Contribute to Open Source

Open-source communities like GitHub, GitLab, and Bitbucket host repositories where you can collaborate with developers worldwide, working on projects ranging from small libraries to full-scale software frameworks.

Why it matters: Open-source contributions demonstrate your ability to work with established codebases, solve real-world problems, and collaborate with experienced developers.

It’s like an ongoing technical interview that can impress potential employers.

In fact, a report by GitHub found that 94% of hiring managers say open-source contributions are a key factor when hiring developers.

Where to Start:

1. Choose a project that aligns with your interests.
2. Look for “good first issues” in open-source projects.
3. Connect with project maintainers by joining the project’s discussion threads or Slack channels to ask questions and gain guidance on contributing.

Beyond the practical experience, contributing to open-source projects connects you with developers across the globe, expanding your professional network and potentially opening doors for future job opportunities.

In fact, we have a whole article on “how to gain coding experience.”

Step 4: Networking and Building Connections

You could say that steps 4 and 5 are interchangeable. Or better yet, do them simultaneously.

In the tech industry, who you know can be as important as what you know.

Networking is about building relationships with other professionals who can offer guidance and even recommend job opportunities.

LinkedIn says up to 85% of jobs are filled through networking.

Building a network of industry contacts increases your chances of getting referrals for job opportunities and staying updated with the latest trends.

Now, onto the bigger problem: how does one build these connections?

1. Attend Industry Meetups and Conferences: Tech and hackathons are great places to meet other developers and industry professionals. Websites like Meetup.com frequently host tech events, especially in cities with thriving tech communities like Barcelona, Berlin, or London.
2. Utilise LinkedIn and Twitter: Social platforms aren’t just for socialising. LinkedIn can be a powerful tool to connect with developers, hiring managers, and recruiters. Don’t be afraid to send a connection request with a thoughtful message.
3. Join Online Communities: Forums like Stack Overflow, Reddit’s r/learnprogramming, or CodeOp’s alumni network are valuable spaces to ask questions, exchange ideas, and network with like-minded individuals.
4. Informational Interviews: Reach out to professionals currently in roles you’re interested in and ask for short informational interviews.

One example is our very own free introduction to coding workshop that we offer once a month, allowing beginners to learn more about the basics of coding and put it into practice with an activity.

We also run a Women+ in Web Development facebook group, which is a home for women+ in the developer space to share resources, job opportunities, scholarships, experiences, and much more.

Building a solid network also positions you well for mentorship opportunities, increasing your chances of being referred for roles in tech without needing a CS degree.

Step 5: Freelancing and Contract Work

Freelancing is becoming increasingly popular, with **a 2018 report by the Freelancers Union stating that full-time freelancers increased from**

17% to 28% of the freelance workforce, while part-time freelancers dropped 9% from 59% to 50% in the USA.

Here’s how you get started:

1. Freelance Platforms: One approach is to take on freelance projects, which allows you to work with actual clients and gather valuable feedback. Platforms like Upwork and Fiverr provide opportunities to apply your skills while building a portfolio.
2. Offer services to local businesses: Approach small businesses in your community that need websites, apps, or technical support. This will allow you to learn while solving real-world business problems.
3. Build a Freelance Portfolio: Like a job-seeking portfolio, your freelance portfolio should demonstrate the work you’ve completed for various clients. Include testimonials or feedback from satisfied clients, which adds credibility to your abilities.

In Europe, freelancers working in web development and data science can expect to earn between €20 and €75 per hour, depending on their experience and the project’s complexity.

In Spain, the average freelancer in tech earns approximately €25-€40 per hour, whereas, in the U.S., rates can be higher, ranging from $30 to $100 per hour.

Source: Upwork Freelance Earnings Report

Step 6: Specialise in High-Demand Tech Areas

Focusing on high-demand tech areas can set you apart from others entering the industry, even if you don’t have a formal computer science degree.

Why Specialising Matters: LinkedIn’s 2023 Jobs on the Rise report shows roles in AI, cybersecurity, cloud computing, and data science have seen the most significant growth.

Specialising in these areas can provide job security and more lucrative salaries. For example, cybersecurity roles are expected to grow by 35% over the next decade** due to the increasing importance of digital security.

Top Areas to Specialise In:

1. Artificial Intelligence (AI) and Machine Learning (ML)
2. Cybersecurity
3. Cloud Computing
4. Data Science and Big Data

How to Specialise:

1. Choose an area that aligns with your interests and market demand.
2. Take specialised courses or bootcamps. For example, CodeOp offers programs focused on data science and AI specifically for women, trans, and non-binary people.
3. Work on specialised projects to showcase your skills in that field.

Step 7: Job Searching and Landing a Role

Once you’ve built up your technical skills through bootcamps, online courses, or self-study, the final step is finding a job. Job searching in tech without a formal CS degree may seem daunting, but it’s possible with the right strategies.

Here’s how we teach our students to do it:

1. Tailor Your Resume and Portfolio:

Highlight your coding skills, projects, and contributions. Make sure your portfolio showcases a variety of projects that demonstrate your versatility and technical abilities.

2. Target Entry-Level and Junior Roles:

Even without a CS degree, many companies are willing to hire junior developers or data analysts if you demonstrate a solid foundation of skills and a willingness to learn.

3. Leverage Your Network:

Many jobs are never posted on job boards. Instead, they are filled through referrals. Use your network—both online (LinkedIn, Twitter) and in-person (meetups, conferences)—to connect with people in the industry.

4. Freelance and Contract Work:

Freelancing or contract work can be a great way to build experience, expand your portfolio, and potentially transition into a full-time role. Platforms like Upwork and Fiverr offer freelance opportunities in web development, app development, data analytics, and more.

As I mentioned earlier, people in the States are actively transitioning from part-time freelancing to full-time freelancing and making a career out of it.

5. Job Boards:

Websites like LinkedIn, AngelList, and We Work Remotely often have job listings for tech roles that don’t require a CS degree.

Tailor your search for junior positions or internships, often focusing more on skills and potential than educational background.

Stand Out During Interviews:

• Prepare for Technical Interviews: Many companies use coding challenges for their interview process. To sharpen your problem-solving skills, practice coding problems on platforms like LeetCode, HackerRank, and Codewars.
• Emphasise Your Projects and Practical Experience: Show employers that even without a degree, you’ve gained hands-on experience through bootcamps, freelance work, or open-source contributions.

With the right approach and consistent effort, landing a job in tech without a CS degree is achievable. And if you are one of CodeOp’s students from our bootcamps, we help you in landing your first dream job.

CodeOp isn’t about teaching you how to program, but to help women, trans and nonbinary people achieve their goals within the STEM industry.

Alright, alright. Let’s be realistic here. The answer can (and will) vary depending on your goals. However, it is true that Python consistently tops the list for newbies—and for good reason.

Python is the best high-level programming language for beginners. Unlike other languages, it allows you to write and execute code without a complex setup or syntax. It’s versatile, widely used across various industries like data science, web development, and automation; and hosts several powerful libraries and frameworks like Pandas and Flask.

It’s not just a tool for building websites or automating tasks; it’s a language powering data science, machine learning, artificial intelligence, web development, automation, and so much more.

In a tech (or STEM) landscape where career flexibility and employability matter more than ever, learning Python opens up a world of opportunities.

1. It’s easy to learn and understand.

Learning a new language that looks nothing like orthographic languages (English, Spanish, etc.) can be one of the biggest obstacles when learning to code.

Python, however, has an English syntax. In other words, the structure of statements follows the grammatical arrangement of words as in an English sentence. It was designed to be concise and easy to read, making it more accessible to first-time coders than many other coding languages.

As such, Python was built to be accessible to beginners. In fact, as any code is read more often than written, Python language’s design is easier to read than some of the other coding languages.

As you can see from the example, Python’s syntax is straightforward and easy to understand, making it a great language if you’ve never coded. It uses English-like words and has fewer complex syntax rules than other languages.

You can accomplish a specific task with fewer lines of code than other languages using Python.

Most importantly, this allows you to focus on learning more complex programming concepts, such as how to write functions, rather than getting bogged down in the details of the language itself.

2. It’s versatile and widely used.

Python is used by companies like Google, Instagram, and Spotify to write their recommendation algorithms. It’s also popular in the scientific community for research in fields such as astronomy.

It’s safe to say that no matter what field you’re in, one way or the other you’ll probably be able to use Python in your work and personal projects. As such, learning Python opens up possibilities for your future career and personal projects.

A. Industrial applications

Lately, Python’s impact on AI and Machine Learning has been growing with innovations in AI tools like ChatGPT and Github Copilot now based in Python. However, its importance as a programming language is not recent. Peter Norwig, Engineering Director at Google, has said that:

“Python has been an important part of Google since the beginning, and remains so as the system grows and evolves. Today dozens of Google engineers use Python, and we’re looking for more people with skills in this language.”

Python.org lists a variety of success stories in other fields and applications that use the programming language. The length of this list proves that Python can be used in an infinite number of ways.

B. Compatibility

Python is a cross-platform programming language. This means it can run code written in one operating system, such as Windows, Mac, Linux hardware, Android and iOS, in a different operating system without any issues.

Another important aspect is its ability to run with other programming languages. A few common examples of Python implementation with other languages are Jython (Python integrated with Java) and CPython (Python integrated with C). These have several benefits.

For example, in some cases, Jython can be faster than standard Python due to its ability to leverage the  Java Virtual Machine (JVM) performance optimisations.

C. Open source

Python, licensed under an Open Source License approved by the Office of Scientific and Industrial Research, was designed to be used freely and distributed for commercial purposes.

The term ‘open source’ refers to a programming language that falls within an open-source protocol’s scope.

This means that the language in an open-source licence is not protected by copyright and can be modified or built upon according to certain conditions depending on which provisions are laid down. The Python Software Foundation acts as the administrator of this licence.

3. There’s a large community and support network.

While programming can sometimes feel like a solitary sport, support from your community is one of the best tools you’ll ever have.

Programmers continue to learn from and build on their predecessors’ successes thanks to online forums, local meetups, and the open-source community. One of the biggest advantages of learning Python as a beginner is the available support and the large global community of people working with Python.

Python has a massive user base because of its open-source tag. There are many contributors constantly working to improve the language and its libraries. This means that if you run into any issues or have questions, plenty of people and resources are available to help you.

For example, Stack Overflow is the largest online community for developers to learn, share their programming knowledge, and build their careers across different languages, including Python. The chart below shows how significantly the Python community on this platform has grown over the years.

The 2022 October report found that Python remains the second most-used programming language on GitHub. Interestingly, Python’s use grew more than 22 percent year on year with more than four million developers on GitHub using it at some point in 2022.

4. It’s great for building real-world applications.

With Python, even if you’re a beginner, you can start building useful applications immediately. Some real-world applications which use Python are:

A. Python for web development

Web development covers all the activities of building websites and web-based software applications. Every website consists of two parts: a client-side, which runs code from your computer’s Internet browser, and a server-side, where the code runs on that Web site.

Source: Tutorialspoint

Without learning a client-side language like JavaScript, you can use Python to rapidly and effectively create Dynamic Web Applications using web frameworks.

B. Python for data analysis

Data analysis aims to find useful information, inform conclusions and support decision-making through data examination, cleansing, transformation or modelling. There are various ways of doing data analysis and it is being used across areas such as business, science or social sciences.

Data analysis plays an essential role in today’s economic landscape, which helps businesses to make better decisions and be more efficient. Python has a range of libraries, such as numpy, pandas and matplotlib, specifically built to help with efficient data analysis.

C. Python in Finance

Financial technology (FinTech) automates and improves the delivery and use of financial services. It ranges from the technology behind your online banking portal as part of your banking services to blockchain applications.

Today, it is used in all areas of finance, like investment management, banking, training and fundraising. Python is used in financial analytics tools for data visualisation and complex statistical analyses, as well as in stock trading platforms to automate the buying and selling of stocks. This helpful article on Python Fintech Projects and Use Cases is a great place for extra details on where Python comes in handy.

5. There are plenty of resources and tutorials available.

Demand for Python programming skills has been growing in recent years. In 2023 and 2024, Python was the most preferred language by developers when they had multiple options.

Source: TIOBE Index

As such, plenty of resources and tutorials are available online. From online videos to interactive coding challenges, there are countless ways to learn Python at your own pace and on your own schedule without breaking the bank!

Free resources can include step-by-step tutorials, short-term courses, online forums, and official Python documentation to help you get started in learning the language. There are also coding challenges and competitions to keep you motivated.

Dr. Angela Yu’s 100 Days of Code: The Complete Python Pro Bootcamp on Udemy is the best resource for getting started in Python. The in-depth explanations and course curriculum in this course are unparalleled.

And I recommend this to all aspiring developers before they join our bootcamp (Data Science or Full Stack) before diving deep into the professional applications.

Of course, you can join our bootcamp directly and start immediately but that’s up to you.

6. Python is compatible with future technologies.

One of Python’s standout qualities is its forward-looking adaptability, making it a prime choice for developers looking to stay relevant.

A. Artificial Intelligence and Machine Learning

Libraries like TensorFlow, Keras, and PyTorch provide robust tools for building AI models, while Scikit-learn simplifies data analysis and machine learning tasks.

Python’s straightforward syntax allows developers to focus on building complex algorithms without worrying about the intricacies of lower-level programming languages.

New advancements in AI, such as deep learning and neural networks, will likely continue to be developed using Python due to the language’s flexibility and supportive libraries.

B. Data Science and Big Data

Data is being generated at unprecedented rates, and companies are eager to harness it for insights.

Python’s vast ecosystem of data processing libraries, including Pandas and NumPy, makes it an ideal choice for managing, analysing, and visualising big data.

Its role in data science is expected to grow as industries become more data-driven and rely heavily on analytics to make informed decisions.

C. Internet of Things (IoT)

Lightweight Python frameworks like MicroPython and CircuitPython allow you to work with microcontrollers and embedded systems. These frameworks allow Python code to run on small, power-efficient devices that form the backbone of IoT networks.

D. Blockchain Development

Its simplicity, combined with libraries like PyCryptodome for cryptographic functions, makes Python a viable option for developing decentralised applications (DApps) and creating smart contracts.

In fact, many blockchain projects, such as Ethereum, have Python-based tools and frameworks that developers can use to interact with the blockchain.

To be fair, this was all just a sneak-peek. Python is far more robust and practical than what I mentioned in this article. Its applications continue to grow wider, reaching robotics, automation and even quantum computing.

7. Questions from CodeOp Community

How long will it take to learn Python?

The time it takes to learn Python depends on your goals and how much time you can dedicate to learning.

Beginners with some prior experience are able to learn the basics in a few weeks, while others may take several months or more to become proficient. It’s important to remember that learning Python is a continuous process, and you’ll likely be learning new things for years to come.

Should I learn Python or JavaScript first?

Python is often recommended for beginners because of its simple syntax and versatility, while JavaScript is more commonly used for web development. Consider your interests and career aspirations before deciding which language to learn first.

It ultimately depends on your goals and what you want to do with programming.

With AI advancing rapidly, you no longer need hours dealing with repetitive tasks like debugging, code refactoring, or even generating documentation.

The key shift we’re seeing is that AI doesn’t aim to replace developers but to streamline processes, allowing you to focus on the job’s most complex and creative parts.

Gone are the days of painstakingly writing boilerplate code or manually scouring for bugs.

Today, AI tools can assist with everything from writing code snippets to automating testing procedures. And the impact? More time for innovation and solving the big problems that matter.

1. Automating Code Generation

AI-powered tools like GitHub Copilot and OpenAI’s Codex can now assist in writing entire blocks of code based on a simple prompt.

Imagine typing a few comments or describing a function, and the AI auto-generates clean, functional code within seconds.

For example, instead of manually writing out every line of code in a CRUD (Create, Read, Update, Delete) operation, tools like Copilot can predict and produce most of the structure, freeing you from repetitive tasks.

While AI can’t handle complex logic or architectural decisions, it excels at automating simpler code, making your workflow smoother and more efficient.

Here’s an excellent paper by Arghavan Moradi Dakhel et al, titled “GitHub Copilot AI pair programmer: Asset or Liability?”

2. Debugging and Error Detection

Instead of spending hours going through logs and code to find the root of an issue, AI can pinpoint potential bugs in minutes.

Tools like DeepCode, Snyk, and Tabnine are great examples of AI-driven platforms that help identify vulnerabilities and logical errors in code. These tools scan the codebase, compare it against millions of other code snippets, and flag common security loopholes, syntax errors, and bad coding practices.

For example, DeepCode’s AI uses machine learning models to identify codebase patterns, flagging inconsistencies or vulnerabilities far faster than a human could. It helps companies like Siemens and BMW maintain high code security and efficiency standards, slashing debugging time by up to 40%.

3. Automated Testing and QA

AI-powered tools can automatically generate test cases, detect bugs, and even predict where problems might occur based on historical data.

Tools like Testim, Functionize, and Applitools use AI to automate functional, regression, and performance testing, significantly reducing the manual effort required.

For instance, Applitools leverages visual AI to compare screenshots of a web application to identify layout or UI discrepancies, making visual testing faster and more reliable.

Large companies like Intuit use Applitools to run visual regression tests on TurboTax’s over 50 UI components and screen configurations across browsers and viewport sizes.

4. Documentation Generation and Management

One of the most mundane yet necessary tasks for developers is writing documentation.

Whether explaining code functions, writing API docs, or detailing system architectures, documentation is critical for maintaining codebases and ensuring other team members or users understand how the software works.

Tools like Kite and NaturalDocs can auto-generate documentation by analysing code comments, function names, and even the logic within the code.

GitHub Copilot, for instance, can write basic function descriptions while generating code, making it easier for developers to maintain well-documented codebases.

5. AI in DevOps Automation

DevOps automation traditionally involves tasks like continuous integration/continuous delivery (CI/CD), infrastructure provisioning, and monitoring.

AI takes it further by predicting system failures, optimising cloud resources, and automating repetitive tasks that slow the development cycle. Tools like Jenkins, Ansible, and Kubernetes increasingly incorporate AI-driven automation to manage complex deployments and scalability.

For example, AI algorithms can dynamically predict server load and scale resources, ensuring optimal performance without manual intervention.

6. AI in Natural Language Processing (NLP) and Chatbots

AI-powered Natural Language Processing (NLP) has given rise to intelligent coding assistants and chatbots that provide real-time support for developers. These tools can answer questions, suggest code snippets, and even debug issues by analysing natural language inputs.

Tools like GitHub Copilot, OpenAI’s Codex, and Tabnine leverage NLP to understand the context within code and offer meaningful suggestions.

Developers can now simply describe what they want to achieve in plain English, and AI models can generate the necessary code.

For instance, with GitHub Copilot, you can type, “create a function that sorts an array of integers,” and Copilot will instantly generate the function.

7. Reducing Development Time for MVPs and Prototypes

AI is particularly beneficial in accelerating the development of Minimum Viable Products (MVPs) and prototypes, a phase where speed is crucial to validate business ideas.

Traditional development cycles for MVPs often require several weeks or months, but AI tools can drastically reduce this timeline.

AI-driven code generators like DeepCode and platform solutions like Bubble (which uses AI to assist with no-code/low-code development) allow non-technical founders or developers to quickly create functional prototypes.

By automating boilerplate code and generating the foundational logic, AI enables teams to focus on testing and refining core features.