The 7 Best Places to Host Data Science Portfolio

As a data scientist, you should have a professional portfolio that demonstrates your abilities and expertise. Possessing a portfolio facilitates the process of informing prospective employers about your experience and credentials. It also facilitates sharing your work and showcasing your accomplishments. Data Scientists can host their work portfolios on a variety of platforms, each with special features and advantages. The top seven platforms for hosting your data science portfolio will be examined in this post.

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Why have a portfolio project?

Creating the time and motivation to work on personal projects might be difficult. But finding a way to combine your love of developing data science portfolio with your working life may be fulfilling, regardless of whether you work a full-time job, are self-employed, or are looking for work. The main arguments for devoting time and energy to developing a data science portfolio are outlined below.

Building and strengthening skills

The data science workflow includes learning to code, creating models, enhancing model accuracy, and deploying models. These are highly sought-after skills, and building a portfolio of work can be an excellent method to improve your abilities and solidify your expertise in the subjects that interest you. Additionally, portfolio projects let you develop talents that aren’t exactly related to your experience, profession, or area of expertise. Developing side projects in computer vision will advance your expertise if you specialise in natural language processing applications. There are countless options.

Showcasing your experience to recruiters

In the hypothetical scenario where two trainee data scientists walk up to a recruiter and say, “I know Python, Machine Learning, and MLOps,” the other responds, “I know all that too, and I applied my knowledge in this project where I scraped data, applied a machine learning model on it, and deployed it as a web-app.” Which candidate will stick out the most is obvious. Your credibility as a Data Scientist can be established through portfolio initiatives. The more diverse your portfolio is, the more you’ll be able to demonstrate to hiring managers and recruiters the range of technical skills you possess.

Demonstrating your soft skills

Building a data science project portfolio demonstrates commitment, perseverance, meticulousness, and a desire to keep learning and getting better. Data science is only one of many professions where these soft skills are essential. More significantly, adding content-based projects to your technical portfolio will allow you to highlight your communication and data storytelling abilities, which will help you stand out as a data scientist.

Taking your first step towards entrepreneurship 

There is only one step between a side project and entrepreneurship, and that is to take the plunge full-time. Several misadventures turned into multimillion dollar startups. Additionally, portfolio assignments are a fantastic opportunity to begin your career as a freelance data scientist.

7 best places to host data science portfolio 

Sharing your research with the data science community can help expand the general knowledge base, attract cooperation, build your brand, and engage you in a bigger discussion. For this reason, it’s a good idea to share information about your work and make sure as many people as possible can see them. Although there are many options available for displaying your data science portfolio, these are some of the top resources and online platforms that can assist you in showcasing your work.

Kaggle

Kaggle is an online forum for data scientists and machine learning enthusiasts. It enables you to search and publish datasets, publish notebooks, work together with other data scientists, and compete with them to solve data science problems. For individuals who wish to put their algorithms into practice, a multitude of datasets are available. This platform’s benefit is that the data is comparatively clean and well-structured. As such, it’s an excellent starting point for gaining experience working on data science projects. Once you’ve registered, you can peruse the several ongoing tournaments across multiple categories:

• A fantastic place to start is with enduring competitions for novices. You can put what you’ve learned into practice by applying what you know.
• Time-limited contests for prizes or recognition are more tough than beginning level.
• Prize-giving contests with a time constraint can be more difficult. Typically, outside organisers like Netflix, Google, and others sponsor them.

Participating in these contests is a fantastic method to advance your technical proficiency and skill development. In order to present your work, you will need a notebook (Kernel) that goes into great detail explaining every aspect of your project so that the greatest number of people can grasp it.

Since the network is well-known for having a large user base, winning rewards might not seem doable for a novice. But you may improve your abilities, gain points, and move up the rankings by taking part in contests and keeping journals. It is simple to think that being a Grandmaster on Kaggle will lead to opportunities for advancement in the data science field.

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Tableau Public

For Data scientists, Tableau Public is an excellent tool for portfolio creation and presentation. It’s made especially for data visualisation, enabling you to make dashboards and visualisations that are interactive and shareable online. In addition to utilising R or Python to construct bespoke visualisations, the platform comes with a wide range of pre-built visualisation alternatives.

The vast user base of Tableau Public, which offers assistance and comments, is another benefit of using it. If you want to advance your career and keep up of the newest methods and trends in the industry, this might be a great resource.

In addition, Tableau Public is free, making it available to data scientists of all skill levels and budgets. It follows that anyone can put together a portfolio that looks professional.

Power BI

With a number of features, Power BI is an excellent platform for data visualisation and is perfect for hosting your data scientist portfolio. These include making interactive reports and dashboards that you can put on your website or share with others via a link. This facilitates the viewing of your work and the understanding of your abilities and knowledge by prospective clients and employers.

Having the flexibility to build bespoke visualisations using R or Python when using Power BI to develop and present your work portfolio is another important advantage. Its vast collection of pre-built visualisation tools can also be used to produce original, polished data vizzes, as we sometimes refer to them.

DataCamp Workspace

DataCamp Workspace is a cloud-based collaborative notebook that lets you examine data, work together with others, and share analysis right away. With Workspace, you can use your browser to write code, analyse data, and share your ideas. Through playbook templates, it provides you with pre-written code samples and over 20 preloaded datasets for analysis. Workspace is available on all OS systems and supports R, Python, and SQL. There are no downloads or installations necessary. Once your projects are created, you can allow people to access them immediately by sharing the URL to your DataCamp profile. Among the excellent initiatives that Workspace hosts are

• The role of Bitcoin in a 3-asset portfolio
• Exploring UK’s Fatal Traffic Accidents
• Forest Fires in Turkey

GitHub

In summary, developers may save, manage, track, and keep an eye on changes to their code repositories using GitHub, a website and cloud service. Version control and Git are two concepts that are related to understanding GitHub. They enable you to track changes made to your projects over time and retrieve certain versions at a later time. Users on the platform can track issues, fork and exchange code, and work together on open-source projects. It’s simple and cost-free to set up a GitHub account and host your portfolio on GitHub pages. Simply adhere to these steps:

• Create an account on GitHub.
• Learn to utilise Git and GitHub. By following this lesson or the Introduction to Git course, you can discover comprehensive explanations and a tutorial on understanding Git and Github.
• Repeat these procedures to upload your website to GitHub pages:
• Open GitHub and make a new public repository called username. github.io, with username being your         GitHub username or the name of your organisation.
• To utilise Git with GitHub on Windows and macOS, just download GitHub desktop if you are unfamiliar with Git commands.
• Once the installation is complete, visit GitHub.com and reload the page. Select “Set up in Desktop” from the menu. Save the project when the GitHub desktop application launches.
• Launch your text editor and start working on your project’s index.html.
• After committing your changes, click “Publish“
• Give your website a theme. WordPress themes won’t work; HTML/CSS templates or bootstrap themes will.

Using platforms such as Github is a good approach to communicate about your work. You can begin uploading your work to Github once you’ve created an account there.All of your projects on Github need to have a readily readable README.md file. Though vital, this is something that programmers frequently overlook. It’s considerably more difficult for the reader to comprehend the purpose of the project if you don’t have a README.md. Here are such instances Project portfolio pages on GitHub

• Chris Tran’s GitHub Portfolio
• Ken Jee’s Example Portfolio

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Personal Website

Another great approach to organise your tasks is to have a blog or personal website. Setting up a website doesn’t have to cost a lot of money, and it’s rather easy. If you choose this path, WordPress is a wonderful place to start, but Wix or Strikingly are other excellent CMS options. Hosting your own website gives you more control and customisation, even though it may be more difficult to attract attention than hosting it on a platform like DataCamp Workspace or Kaggle. Additionally, you can rank highly in Google searches if you put a lot of effort into optimising your SEO.

Medium (and social networks)

It’s critical to share as much as you can about your efforts. In addition to your own website, you can use blogging platforms for content-based portfolio projects. One of the greatest places to share your creations with a larger audience is Medium. Additionally, you may increase the visibility of your projects and establish your credibility as a data scientist by posting on social media sites like Reddit, Quora, LinkedIn, and Twitter.

Conclusion

Regardless of which platform you choose, it is critical to keep your portfolio up to date with your most recent projects and achievements. This will help you stay up to date and relevant, but it will also demonstrate your abilities and potential to prospective employers. A strong portfolio that is updated frequently can help you progress in your work as a data scientist.