A is the brand new resume — it’s what substitutes for real work experience.
But immediately, your projects are either useless filler otherwise you’re simply not taking them seriously, and that’s why you’re not landing interviews.
So on this , I’ll break down the essential project types that top-tier corporations search for, so you’ll be able to stop submitting dead-end applications and begin scheduling interviews.
Let’s make your portfolio the interview magnet it must be.
3-5 Easy Projects
Absolutely the baseline in your portfolio is 3–5 “easy” or “easy” projects.
This may not necessarily move the needle in getting hired, but it can give your portfolio initial weight.
Consider these easy projects because the “warm-up reps” on the gym. They aren’t the heavy lifting that builds serious muscle, but they establish the elemental mechanics, consistency, and discipline needed before you tackle the most important challenge.
The first goal of those projects is to get you creating and constructing and not using a guided tutorial, and to essentially get you pondering creatively about learn how to solve problems.
It’s also about “optics” and ensuring that your resume, GitHub, and LinkedIn profiles appear lively and well-populated.
Nevertheless, do take a couple of month to construct these smaller projects, ensuring they’re of sufficient quality and never swiftly generated with ChatGPT.
Aim to construct a wide selection of projects, each using different tools, datasets, and machine learning algorithms.
For those who want some inspiration, take a look at this repo I made nearly 5 years ago, which accommodates examples of those easy projects after I was attempting to get my first job.
GitHub – egorhowell/Data-Science-Projects: A choice of small Data Science Projects.
github.com
One thing I’ll say is that these projects are probably below par by today’s standards, as the sector is becoming increasingly competitive.
So, below is a listing of key objectives that your easy projects should meet to make them worthwhile:
End-To-End Project
If you need to work in machine learning, it’s essential to have the ability to deploy your algorithm.
You’ve got probably heard this sentence from me and others multiple times.
Having essentially the most sophisticated, fanciest state-of-the-art transformer model means absolutely nothing unless it’s making real-life decisions.
Corporations and hiring managers know this, and admittedly, all they care about is whether or not your model is saving or making them money and whether their underlying profit is increasing.
So, you need to showcase to potential employers that you already know learn how to construct and ship an algorithm end-to-end in your portfolio.
Your project should ideally include the next:
This project is usually the toughest for beginners to create since it does require some up-skilling and learning a little bit of software engineering.
A few of the things you have to to learn are:
What I don’t want you to do is get intimidated and overwhelmed by the list.
Start small and learn the essentials as you go; you actually is not going to need to make use of the whole lot I just mentioned.
And as all the time, make it as personal as possible; it will keep you motivated, and it’s a a lot better talking point in interviews.
For those who need a real-life example, then take a look at considered one of my previous YouTube videos where I walk through an entire end-to-end project I created that forecasts stock prices after which optimises my portfolio.
Research-Focussed Project
I often recommend that folks add some research element to their portfolio.
One method is to re-implement a research paper they’re fascinated with.
You’ll learn a lot from this process:
And one of the best part is that almost all, literally 99%, of candidates will not be doing this, so that you will immediately stand out.
Some useful web sites to search out papers:
Re-implementing a paper may be very hard. I actually have tried several times up to now, and I still couldn’t quite get it 100% correct, but I learned a lot from that process.
One other technique to add research into your portfolio is thru reading and distilling papers either through writing about it online and even through a journal club.
The latter is what I arrange at my previous company, and it was useful. I presented a wide range of papers reminiscent of:
It taught me learn how to translate among the most technical topics on this planet in the meanwhile right into a digestible 1-hour presentation.
It is a skill that corporations really desire, as many practitioners in the sector don’t have it.
For those who currently don’t work in an organization where you’ll be able to arrange something like this, there are numerous Discord and community groups on the market.
One group I like to recommend is Yannic Kilcher’s Discord. He’s a machine learning researcher and engineer who creates YouTube videos breaking down research papers.
Write Technical Articles
Most individuals assume their articles should be “groundbreaking.”
For those who have a look at mine, many of the posts are about fundamental statistical, data science and machine learning concepts.
To this point, I actually have written well over 150 technical and over 60 career-based advice articles.
These began off purely for myself as a way to learn more concerning the field; I didn’t care if people liked them or not, as they were solely for me.
That is the attitude you must have as well.
Start by documenting what you’re currently learning or need to learn. No have to overcomplicate it.
Having a blog brings so many positives to your profession and talents:
Your blog is a passive income generator in your profession. The sooner you spend money on it, the higher the payoff.
I like to recommend you begin blogging here on Towards Data Science, because it’s very easy to make use of, has a big data science community, and already has an in-built audience.
There are other, more developer-focused platforms, reminiscent of Hashnode, or you’ll be able to even blog on your personal website, utilising platforms reminiscent of WordPress or Ghost.
If you need to learn more, I actually have a complete post about learn how to start and write a technical blog that you may take a look at below:
Now that you already know the precise projects that turn your portfolio into an interview magnet, there’s only one final piece of the puzzle: the way you present it.
Most individuals just throw a GitHub link on their resume and hope for one of the best, but in case you try this, you’re missing out on an enormous opportunity to focus on the business value of your work.
To learn exactly learn how to showcase your portfolio, see considered one of my previous posts below.
I’ll see you there!
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