Creating the Data Science Portfolio

Learning data science skills won’t get you too far unless you can also apply those skills in practical ways. One way to display your applied knowledge in the field is through working on projects and collecting them into a portfolio that you can share with potential employers and collaborators. While the data science portfolio can take on many forms, it usually displays data and deliverables through a platform that is easily accessible. Creating a data science portfolio is an important part of receiving training or advanced education in the field.

What is a Data Science Portfolio?

A data science portfolio is a platform or collection of materials that display your knowledge and capabilities in the data science industry. Data science portfolios showcase projects, skills, accomplishments, and other examples of your knowledge and ability to work with data. For data science students who are new to the industry (or professionals who want to shift to a new career), the portfolio demonstrates your experience even if you haven’t worked within the field before.

Similar to a license or certificate, a portfolio can be used as proof that you are well-trained and understand how to work with data science tools. The portfolio is a complement to your resume or job materials. Portfolios also demonstrate your interest in your field of work. By taking on projects or skill-building courses outside of a traditional workplace setting and adding the results to your portfolio, you can show potential employers that you are a self-starter who is committed to staying up-to-date on industry trends and improving your craft. 

Types of Data Science Portfolios

The style and format of your data science portfolio will depend on the type of portfolio you want to develop, how it will be shared, and your audience. While some portfolios are geared towards the practical application of data science tools and techniques, other portfolios are created for a specific job or industry. The following list outlines three types of portfolios that you can develop: project portfolios, industry-specific portfolios, and skills-based portfolios.

The Project Portfolio

The project-based portfolio is one of the most common types of portfolio in the data science industry. These portfolios include examples of the different data science projects that you have worked on and deomonstrate the creation of key deliverables which respond to real-world problems. Project portfolios are often the final project of a data science class at both degree-granting institutions and certificate-issuing programs. The project portfolio is an excellent place for data science students to start. By building your skills and communicating them through projects, you can demonstrate your capabilities to potential employers regardless of your industry experience.

The Industry-specific Portfolio

For Data Scientists who have built a career, or those who are interested in shifting career paths, the industry-specific portfolio is useful. Industry-specific portfolios present work centered on a particular subject area or data science-related industry. This type of portfolio should embody the best practices, or methods, of presenting data to audiences within your field of interest. 

For example, if you are interested in pursuing a career as a Financial Analyst, you may want to create a portfolio with business intelligence reports or dashboards. If you want to pursue a career as a Research Data Scientist, you may want to create a portfolio with links to articles and experiments or statistical models. Creating an industry-specific portfolio requires a combination of research, experience, and additional knowledge about the field you want to work in.

The Skills-Based Portfolio

The skills-based portfolio is useful to both data science beginners and industry professionals. This type of portfolio displays data science skills and tools that either correspond to a position or are up-to-date with the most desirable skills in the industry. Displaying your skills in a portfolio could be as simple as beginning a data science blog, creating visualizations with the latest modeling software, or even uploading a screenshot of sample code that you wrote in a popular programming language. Skills-based portfolios are an excellent way to demonstrate the skills you may learn outside of your training or skills that you have not yet demonstrated in a data science project.

How to Create a Data Science Portfolio

It is important that your portfolio can be easily shared with others. Developing a professional website or online collection of resources is one way to achieve this. You can create a website based on a template or even build your own website to display your skills. While it is easoer to create a website through any number of web development platforms, creating your own unique website does the added work of displaying your skills in both data science and web development. 

After you decide type of website that you want to create, you can identify the type of portfolio that you need. It is also possible to include multiple pages or sections on your website, each of which can display a different type of portfolio.

After identifying the type of portfolio that you want to develop, you should research the job requirements and skills for positions you’re interested in. Consider how to demonstrate those skills within your data science portfolio. Once you have included your projects, skills, or other information within your digital space, you can also keep building on your portfolio over time to further demonstrate your commitment to the field. 

Interested in Creating a Data Science Portfolio?

Creating a data science portfolio is an important part of building a career in the data science industry. Many of Noble Desktop’s data science classes include professional development training, as well as hands-on learning components which result in the creation of a final project or data science portfolio. The Data Science Certificate includes beginner-friendly instruction in programming languages and analytics, culminating in the development of a project-based portfolio.

The Data Analytics Certificate is a project-based program where you can work with real-world data. At the end, you’ll build an industry-specific data science portfolio. This type of portfolio development helps you display your skills working with the data from various industries, demonstrating diversity and flexibility in your ability to solve complex problems. Students new to the data science industry (and more experienced professionals) can both benefit from learning how to better display their projects and skills through the creation of a data science portfolio.