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7 Platforms To Host Your Data Science Projects To Make A Killer Portfolio

7 Platforms To Host Your Data Science Projects To Make A Killer Portfolio

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lekhana
·Nov 4, 2022·

6 min read

Data science is a field that's expanding by leaps and bounds. Each day brings with it new developments, new techniques and more data. That's why there are now so many different platforms to host your data science portfolios – both free and paid. As a budding data scientist, it's essential to carefully choose which platform(s) you decide to use. In this article, we'll look at some of these top data science hosting platforms that students can use to host their portfolio data to gain insight from their analysis skills. Some of these platforms support advanced collaboration and get additional SEO benefits.

What Is a Data Science Portfolio? In today's world, where technology is being used to understand human behavior, data scientists need to have their portfolios. A Data Science portfolio is a collection of data science projects that can be a substantial asset for a data scientist to showcase their skills and abilities to potential employers.

What's The Point Of Having A Portfolio Project In The First Place? In today's data-driven world, having a data science portfolio of your work is essential. You may be an expert in one field, but that doesn't mean you don't have skills in other areas—and the more diverse your data science portfolio is, the more likely you will be hired. Finding the time and desire to focus on personal projects might be challenging. But, aside from the fact that it can be satisfying to balance your working life with your enthusiasm for creating data science projects, there are many ways to do it.

A data science portfolio is a worthwhile investment of time and effort for several reasons:

Showcasing your expertise to potential employers Showing your soft skills, such as presentation and communication skills Developing and Improving Skills Helpful if you want to work as a freelancer

Places To Host Your Data Science Portfolio

Kaggle: Kaggle is a platform for data scientists and machine learning enthusiasts to collaborate online. It allows you to work with other data scientists, identify and publish datasets, publish notebooks, and compete with other data scientists to solve data science problems. You may find many datasets from which to build your algorithms. Data on this platform is well-structured and tidy, which is a huge plus. Thus, it's a beautiful place to start if you're interested in learning more about data science. After signing up, you'll be able to browse through the many competitions now taking place in several categories:

Beginners can benefit from long-lasting competitions. You can practice your acquired knowledge here. With rewards, time-limited competitions might be more difficult. Netflix, Google, and other external organizers often support these events.

GitHub: Developers, coders and data scientists use GitHub to keep track of their code repositories and make changes as they see fit. It is the best platform for a data scientist since it allows people to collaborate worldwide. To better understand GitHub, familiarity with the concepts of version control and Git is a must which you can learn in a data science training in Bangalore. A basic GitHub account is all that's required to begin showcasing your data scientist portfolio.

Create an account on the GitHub website. Learn all you need to know about GitHub's features and functionality. Basic information can be found in GitHub Docs. Use GitHub pages and upload your site by setting up a new public repository with your specified username. Refresh the GitHub website and complete the installation on macOS and PC GitHub versions. To get started, open a new tab and type index.html into your text editor. When you're finished, press the publish button.

Social Media Platforms: As a data scientist, you can gain much from social media, even if you don't use it for everyday tasks. There are a few places where organizations and employees may meet, talk, and even look for work. Twitter and LinkedIn are great places to find and engage in exciting conversations. As a result, your former job history can be shown on LinkedIn, allowing you to connect with those interested in it.

People who make a positive contribution to the community are more likely to be approached by potential employers. Avoid self-promotion and, instead, just be yourself. If you spam, your reputation will be degraded. FOCUS ON SHARING YOUR KNOWLEDGE Expand your network and reach out to new individuals from other sectors and viewpoints to acquire a more comprehensive picture. To raise your profile and reach a wider audience, discuss your personal experiences and examples of similar situations. This will help you get customized job alerts via LinkedIn.

Data Camp Workspace: Datacamp Workspace is an interactive cloud-based notebook that enables you to analyze data, communicate with others, and immediately publish research. More than 20 preloaded datasets are available for analysis and playbook templates with pre-written code samples.

Workspace is accessible for all OS systems and supports R, Python, and SQL. It does not need to be installed or downloaded in any way. In addition, once you've created a project on DataCamp, you can share a link to that project with others.

Personal Website: One of the best ways to concentrate your projects and efforts is by creating a blog or personal website, which doesn't require a significant investment in time or money.

It's a good idea to start with WordPress, but a CMS like Strikingly or Wix will work just as well. When opposed to a service like DataCamp Workspace or Kaggle, hosting your project on your own site gives you greater flexibility and customizability. Additionally, if you put in the time and effort to enhance your SEO, you may reach the top of Google search results.

Blog platforms can be used in addition to your own website for a content-based portfolio project. For example, you can share your work with a much larger audience with Medium.

Google Cloud Platforms: Great companies these days are shifting to or are already leveraging cloud data storage and processing capacity. Providing some practical instances of utilizing your expertise in this area is a good idea. The Google Cloud Platform (GCP) includes several tools for exhibiting your work. Various projects can be created free using the GCP's free usage option.

DrivenData Drivendata.org is an excellent place to start if you want to show off your expertise while also contributing to solving societal problems. Similar to Kaggle, this website provides a platform for data science competitions with data sets and leaderboards, but the focus here is on a social issue that can be solved by data science. These competitions are based on fascinating data sets that range from beginner-friendly to complex.

Conclusion

The world of data science is expanding rapidly, and there are plenty of places to find various jobs if that's what you're looking for. The point of this article is to promote awareness about what's out there in the data science portfolio hosting space so that budding data scientists can use it to their advantage. They are all pretty similar with differentiators.

Whatever you choose to do, try not to spend too much time worrying about your data science portfolio and how it will look on any given site. That's less important than having a polished final product that demonstrates your skills, knowledge, and experience. Besides this, if you're at a point where you need to improve your data science and AI skills, then join Learnbay’s data science course in Bangalore, designed in collaboration with IBM. Here, you can build 15+ domain-specific data science projects with the help of experienced experts, which will enhance your portfolio.

 
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