Forem: Alvin 💻

Transitioning From the Frontend to Full Stack Web Development

Alvin 💻 — Mon, 06 Feb 2023 07:04:18 +0000

I've been learning front-end web development for a while now. My stack now consists of four primary technologies: HTML, CSS, JavaScript, and React. On top of that, I also work with Sass and Tailwind CSS and, in a previous life, Boostrap.

However, while my front-end development skills can take me far, learning about the backend can help me go even further. That's why I started learning server-side development using Node and the Express framework. In other words, I'm going full stack.

I started learning Node using Maximilian Schwarzmüller's NodeJS - The Complete Guide (MVC, REST APIs, GraphQL, Deno). I haven't finished yet, but the course is pretty thorough, starting with the basics and building from there. On top of that, I've also been reading numerous articles because I learn best by combining videos and articles/books.

Building projects is just as important, so I took a simple 2-hour course on YouTube from JS Mastery that builds an AI image generator web app using the MERN stack (MongoDB, Express, React.js, and Node). The course has a good overview of creating real-world full-stack apps from scratch to deployment.

With this knowledge, I'm currently building a URL shortener, part of Frontend Mentor challenges. You can check out the challenge on Frontend Mentor and give it a try if you want.

However, since I'm learning full stack, I want to build a backend from scratch and an API that shortens URLs (instead of using available ones). You can check out the project's progress on my GitHub.

How I’m Learning Data Structures and Algorithms as a Newbie

Alvin 💻 — Sat, 28 Jan 2023 08:47:09 +0000

Data Structures and Algorithms is one of those things that you know you need to learn but never plan for it. Or just start and give up along the way because, let's be honest, DSA is tough. However, DSA can help in sharpening problem-solving skills, which, ultimately, can help you become a better developer.

And, unfortunately, when it comes to interviews, problem-solving skills are mainly prioritized—furthermore, companies test that by using DSA questions. In light of this, I have decided to teach myself DSA from the basics. Here is how I am doing it.

Me vs. Data Structures and Algorithms

My interest in DSA started when I joined a certain boot camp last year. It was mainly about DSA. I had already done a DSA unit at my university, but it was several months earlier. Of course, I had already forgotten many of the concepts.

I relearned the basics at the bootcamp, and then I stopped revising the same, and that's how I almost forgot everything again. After doing some research, I realized that developers who are good with DSA regularly practice.

They don't just learn DSA and move on to other things, then come later and still remember everything. Well, this is no surprise, it applies to pretty much everything. To apply the same I'm using so-called spaced repetition, where you repeatedly study difficult concepts until they stick.

How I'm Studying Data Structures and Algorithms

Here are my approach to learning DSA:

Setting aside an hour a day

Usually, I study DSA first thing in the morning (after breakfast and the usual preparations, of course).

Reviewing what I learned yesterday first thing in the morning

Every day, I start my day by reviewing what I learned yesterday. If I tackled a problem, I'd try to remember how I solved it and write down my solution on paper.

If I didn't solve the problem and looked up the answer, I'll still try to tackle the problem again individually to see if I understood the concept. This process might take a few minutes, or worse, the entire hour!

Spaced repetition

After a few days, I'll review a concept I learned or a problem I tackled to refresh my memory.

So far, I'm pretty happy with the results. I'm finally getting the hang of solving DSA-related problems.

Resources

Here is a list of resources I'm currently using:

Cracking The Coding Interview by Gayle Laakmann McDowell - This book has a large section dedicated to Big O. Also, it goes further to teach about different Data Structures that you'll find in interviews.
JavaScript Algorithms playlist - Codevolution/YouTube
JavaScript Data Structures playlist - Codevolution/YouTube
Neetcode - A structured way for tackling essential Leetcode questions (with video solutions (in Python) and code written in several programming languages like JavaScript, Java, Python, and C++)

Notice a typo, error, or additional information worth sharing? Comment below. I'd love to hear your feedback.

I Took (and Passed) Four LinkedIn Assessment Tests: My Experience

Alvin 💻 — Mon, 23 Jan 2023 21:44:54 +0000

I just resurrected my LinkedIn account after several months. I decided to go under the radar for a while in 2022 because … well, I can 👀. After reactivating my LinkedIn account, I embarked on a journey to update my profile to align with my life.

One of the first tasks on my LinkedIn profile refresh project was to update my skills. That's the point where I bumped into LinkedIn Skill Assessments. I decided, why not? Let me give this a try.

As a result, here's my experience with LinkedIn Skill Assessments and everything you need to know about it.

What Are LinkedIn Skill Assessments Tests?

The pitch is simple; you take a skill test made of multichoice questions to demonstrate to potential employers that you're conversant with what you claim to know.

Typically, a LinkedIn Skill Assessment test includes 15 questions, and you're given a strict timeframe for attempting each question. Plus, you have to complete the test in one sitting.

You're given about a minute and a half to answer each question. Once the timer runs out, you can't answer a question. You have to go to the next.

To pass a LinkedIn Skill Assessment, you need to score in the top 30%, which earns you a badge.

Where to Find LinkedIn Skill Assessment Tests

You can check LinkedIn Skill Assessments by navigating to your profile and scrolling down to the Skills section. You'll see a Demonstrate Skills button in this section that you can select to navigate to LinkedIn's Skill Assessments.

Alternatively, use this direct link: LinkedIn.com/skills-demonstration/skills.

My Experience with LinkedIn Skill Assessment Tests

The same day I bumped into LinkedIn Skill Assessment tests; I did four tests; HTML/CSS, Frontend web development, React.js, and JavaScript. I aced them all, so I have the badges on my profile.

To test the waters, I started with HTML/CSS, and I quickly realized it was all about basics, mostly syntax and the building blocks of a language. That's why I aced three other assessments in a single sitting.

That's not to say advanced concepts aren't included. However, even if you're asked about an advanced concept like error boundaries in React or code-splitting, they keep it basic. You only have a little time (about a minute and a half) to answer every question.

In addition to questions about concepts, you can also be given sample code with a bug. In this case, you need to pick an error-free version that solves the bug in question. I found such questions challenging because you have to understand the code first. Take longer to understand the code, and your time will run out.

Can You Retake a LinkedIn Skill Assessment Test?

You won't earn a badge if you don't score 70% or above. The good news is if you fail a test, LinkedIn gives you a second chance. But with a catch. The company says you can retake the test within six months.

You don't have to worry about it since the platform won't show that you failed a test.

A LinkedIn Skill Assessment Tests Worth It?

You might be wondering whether taking these tests is worth your time. Well, I'm guessing no employer will solely rely on your LinkedIn Skill Assessment badges to offer you an opportunity. You must also be able to demonstrate your skills to them.

However, I think these badges might come in handy in helping your LinkedIn profile stand out. That's what I'm telling myself so I don't feel bad about potentially wasting my time taking the tests.

Notice a typo, error, or additional information worth sharing? Comment below. I'd love to hear your feedback.