No experience? No problem!: Best practices when building a portfolio.
Read Time ~ 4 Minutes
If you have tried to apply for a job recently you most likely seen a very similar post:
This is from the requirements section of an ENTRY LEVEL data analyst position off of a certain job board. It took me about 30 seconds to find and there were a lot more like this one. While the Bachelor’s degree is a topic for another discussion, I want to focus on the experience requirements. This is a frustration that I faced when I was transitioning into my new career in AI and still gets me upset when I see it.
I need experience to get a job but I can’t get a job without experience!
Seems like a losing situation but there is hope and something I did in order to give myself a fighting chance.
A portfolio full of personal projects!
Here’s three things in order to help you build a robust portfolio.
Collect the data yourself
One of the worst things you can do when creating a personal project is to use data that has been analyzed and modeled ad nauseam. Something like performing a binary classification on the Titanic dataset will not make you stand out. It might even hurt you.
While those types of datasets are great for practice because you can see how others tackle the problem, they don’t provide much value to a portfolio.
The best thing you can do is to collect your own data and the number one way is through web scraping. Web scraping is the act of extracting data from webpages. Everything you see through your browser can generally be scraped, with varying degrees of difficulty, and because it is not readily available the chances of a recruiter seeing a similar project in someone else’s portfolio go way down. As an added bonus, the act of web scraping itself shows experience in data engineer. If you are interested take a look at using Python’s requests and Beautiful Soup libraries.
If web scraping might be a bit to advanced there are plenty of websites that host datasets of varying kinds. Here’s a few to get you started:
These are just a few of the many websites with tons of free datasets for you to base a project off of.
Complete a project you care about
Nothing is worse than trying to force yourself to do something you don’t want to do and that goes for projects as well!
When you do force yourself, it shows in your project. It shows in the way you talk about it, the quality of the work, and the level of detail the project takes on. I am not saying you have to love it, but it should at least be interesting to you.
To find a project that might interest you take a look at what things interest you in general. Once you know that then go search for a dataset along those lines. For example, I love to unwind after work by playing video games so I might try to look for a dataset that has something to do with video games. Maybe a project about E-sports betting and seeing if I can predict who will win in a particular game or maybe some sentiment analysis on a new game that just launched and predict whether it will flop or succeed in the next 6 months.
If you are interested in anything there is most likely a dataset on it. Go find it! Or better yet, collect it yourself!
Create a simple and detailed version of your project
This may seem a bit odd but it’s a good idea to create two versions of your project, a simple one that any layman can digest and a detailed one where all the beautiful engineering and analysis is on full display.
The reason being because your portfolio might not just be viewed by people in the same field as you but by others that might be less technical. The person most likely to fall into that category would be the recruiter you have to initially get past. I am not saying that every recruiter will go through your portfolio, but if they do, you want to make sure there is something in there that they can understand.
It doesn't have to be anything major. Just a simple presentation explaining what you accomplished.
And if they want to dig a little deeper they will see all the technical details on how you accomplished the project.
Wrapping it up
Experience isn’t everything and a beautiful crafted portfolio can make up for the lack of it. We all have to start somewhere!
I hope these tips will help to further your career in AI.
Until next time.
Andrew-
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Head over to the contact page and drop me a message. I will be more than happy to read it over and see if I can provide any insights!
