Building a Data Science Portfolio

Posted in: Opportunity Fund, Skills Development


This summer, I decided to invest my time in building a data science portfolio, and in this blog, I'm excited to share my journey and insights with you. Building a portfolio might sound intimidating, but with the right approach, it can be a rewarding and enriching experience.

Getting Started:

To start your journey towards building an impressive data science portfolio, you'll need a few key ingredients:

Projects: The heart of your portfolio will be the projects you've worked on. Begin by gathering your relevant coursework, code, and any other work you want to showcase. If you're like me, you might have Rmarkdown or Python projects from your coursework. Additionally, you can explore online platforms like Codecademy, which offer data science and machine learning courses with hands-on projects.

I also did the Codecademy Data Science- machine learning course which has three more python based projects

Skills: Before diving into the technical aspects, make a list of the skills you want to highlight. Data science encompasses a wide range of competencies, from data analysis and machine learning to data visualization and domain expertise. Identify what you excel at and want to emphasize.

Creating Your Portfolio:

Now, let's dive into the process of creating your data science portfolio. I chose to host my portfolio on GitHub. Here's how I did it:

Select a Template:

I used to select mine. I found a visually appealing and customizable template that suited my style. Once you find one, download it!

Customize Your Template:

After downloading your chosen template, open the index.html file in your preferred code editor (I use Visual Studio Code). To see how your changes affect your website, open it in your web browser and refresh the page. Most templates are easy to edit, allowing you to replace text and images with your own content.  

Structure Your Portfolio:

I organized my portfolio into four main sections: About me, What I'm good at, My work, and Contact me. Use these sections to introduce yourself, highlight your skills, showcase your projects, and provide a way for interested parties to get in touch with you. You can check out my portfolio for inspiration!

Showcasing Your Work:

To display your projects on your portfolio, save them in the assets folder of your template. You can use HTML code like this to embed PDFs or images of your work on your webpage:

<object data="assets/MyWork1.pdf" type="application/pdf" width="100%" height="500px"></object>

Publishing Your Portfolio:

Once you're satisfied with how your portfolio looks and feels, it's time to make it live on the internet! Follow these steps to publish your data science portfolio:

Create a GitHub Repository:

Create a new repository on GitHub with a name like '' For instance, mine is ''

Upload Your Work:

Upload or push the content of your portfolio to this repository.

Configure GitHub Pages:

In your repository's settings, navigate to the "Pages" section. Set the source to "deploy from branch," and you can then launch your website. Your portfolio will be accessible at ''

I hope this has been helpful!

Posted in: Opportunity Fund, Skills Development


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