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April 9, 2024 - 6 minutes

Build Your AI Portfolio: Showcase Your Skills

Discover how to create an AI portfolio that showcases all you bring to the table.

Ironhack

Changing The Future of Tech Education

Articles by Ironhack

Artificial Intelligence

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You know that boasting artificial intelligence skills is quite the flex, right? After all, there’s probably never been a technology that’s transformed the world more (at least in recent memory!) than AI. What sets AI apart from other cool technologies, however, is the ability to be used in a vast range of applications by techies and non-techies alike, meaning everyone, regardless of their area of expertise or sector, can benefit from learning artificial intelligence skills and tools to propel their careers forward.

But as AI skills are relatively new and lots of people are learning on their own, the actual process of adding these skills to your resume or portfolio and showing hiring managers what you can do is a bit more complicated. 

In this article, we’ll discuss the basics of creating an AI portfolio that showcases your skills, in addition to a quick recap of some of the main AI skills that you can look forward to adding to your toolbox in the near future! 

Let’s dive right in. 

AI Skills for Your Portfolio 

The first step in adding AI skills to your portfolio is deciding which ones (because there are a lot!) are of interest to you and, of course, which make the most professional sense. For example, you may be fascinated by the idea of AI image creation and coming up with innovative and transformative graphics, but don’t really have a need for that in your current role. So before you get carried away with the incredible range of AI tools, make sure you center your efforts in those that interest you, but are also good ways to accelerate your career. 

There are quite a few AI skills out there, but these are some of the most common ones that we’ve been seeing soar in demand lately:

  • Python: the majority of AI tools are backed by Python and even if you don’t become an expert, understanding the basics of Python and how it’s applied to artificial intelligence and machine learning tasks can make you an incredibly valuable asset to your team. Capable of applying Python in AI from conceptualization to deployment, you’ll be able to apply what you’ve learned to real world projects. 

  • OpenAI’s APIs: OpenAI’s popularity has skyrocketed, thanks to the release of ChatGPT and if you’re looking for a quick and easy way to create your own AI product prototype that meets your company’s specific needs. As you become well-versed with OpenAI’s APIs and the associated skills, your prowess in the field of AI will only grow. 

  • Data analysis: basing your decisions off of data is simply the right choice and with the help of AI, the data you can collect, analyze, and visualize will reach entirely new heights. With the help of AI tools, you’ll be able to build models to conduct different kinds of analysis, helping you better understand the data with which you’re working. 

  • UI design: the creative power of AI is unmatched and that’s exactly why UI and product designers alike will benefit from a strong understanding of how AI can transform tools like Figma AI and Canva into your new best friend. With a better grasp on the creativity of AI, you’ll be well on your way to creating visually appealing and user-friendly interfaces that users love to return to.

  • Image creation: looking for the perfect image or graphic but just can’t find it? Luckily for you, artificial intelligence is quite skilled in image creation, but it takes an expert to know how to create the perfect image–and one that makes sense given the context! Transform your marketing materials, social media content, and branding images with the help of AI image creation. 

Creating Your AI Portfolio 

Now that you’ve decided which AI skills are right for you and planned out how you plan to add them to your knowledge base, it’s time to start thinking about how you can create an AI portfolio that reflects your skills and knowledge. 

As you know, a portfolio differs from a CV in that it provides actual examples and proof of the work you’ve completed, instead of just words on a piece of paper. Many employers ask for them because they help your potential boss get an idea of what you’ve worked with, how you work, and what your work ends up looking like. 

Therefore, it’s important to have your portfolio ready to go when you’re applying to jobs; you also need to ensure it accurately reflects your abilities. To do so, make sure you include the following.

Project summaries 

When detailing the projects you’ve worked on, it’s crucial to include a variety of different projects that showcase various skills; for example, you’ll want to show you’ve worked with data analysis, programming languages, and image creation and that you’re well-rounded when it comes to using AI in your projects. 

Don’t get carried away with going into the nitty gritty of absolutely every detail of the project; during interviews, potential employers will ask any questions they have, but take a sentence or two to explain the most important aspects of the project. 

Work samples 

With the brief explanation of what the project was all about out of the way, it’s time to show your work! Here, you can include pieces of code you’ve written, links to finished projects, or screen captures of images you’ve created or data you’ve analyzed so that your prospective employer can see how your work has had a real life impact. 

It may be tempting to include a ton of examples here, but prioritize the work that you’re proudest of or had the biggest hand in to ensure that you’re putting your best foot forward. 

Case studies

In the field of AI, there are quite a few complex projects that are impossible to summarize in just a screen capture or a few sentences. Therefore, if you have any projects that you’ve worked on from the very first moment until completion, the case studies section of your portfolio is the ideal time to include it. 

If you choose to include a few case studies, you can go into more detail regarding your work, explaining your decision making process, challenges, and final results. 

Results 

The last section of your AI portfolio should be very straightforward and easy to understand: the results. Here, you want to showcase not only what you’re capable of, but also the impact your work has had. For example, you could explain that using AI tools to help your data analysis led to improved customer loyalty or using AI to generate social media graphics increased engagement. 

This section is a snapshot into the value that you can bring to a team and is a very simple way to communicate said value to a potential employer.

There’s never been a better time to prioritize learning AI skills, elevating your skills and becoming an all-around more valued employee and professional. No matter your industry or area of expertise, learning the basics of AI can help you increase efficiency, save time, and automate tedious processes.

That’s exactly why Ironhack has introduced our new AI School; we’re looking to give professionals the knowledge they need to add AI skills to their arsenal in just a matter of weeks. 

Sound like a good fit for you? Check out what we offer and get started today.

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