How Beginners can Create a Data Science Portfolio
Data science portfolio can simply be put as a proof of work or your expertise, it is what lets your work speak for itself, hiring professionals get to encounter a lot of curriculum vitae on daily bases but what makes your resume worthy to keep going over is your portfolio, it helps your prospective employers decide if you are a great fit for the role based on the work displayed.
Times are changing and no matter the data science aspect you want to major in, it is recommended you have a portfolio, besides having a portfolio to show when searching for a job, it also helps you stay on track with your progress so far and that can be a form of encouragement.
Your data science portfolio can be in physical form or can be digitized but it’s an era where technology has taken over so it is better to have an online portfolio that you can easily share when needed.
To make it professional you can host your portfolio on your domain which makes it unique but there are free hosting platforms such as NETFLIFY, HEROKU . There are different websites where you can build your portfolio for free such as WORDPRESS, BEHANCE, ADOBE PORTFOLIO, CREVADO, PORTFOLIOBOX etc.
Below are 3 strategies a beginner in data science can create an amazing data science portfolio.
1. Build small projects
As a beginner in data science, it is very understandable not to have worked with clients yet, but you should include those small projects you have worked on, from those in-house projects to personal projects. There are a lot of platforms where you can get datasets for practice such as Kaggle. com, Zindi.com, etc.
2. Add certifications
Certifications have a way of showing commitment and authenticity, it is highly recommended that you add the certificates obtained from all your training to your portfolio as it shows that you started a course and saw it to the end.
3. Add explanations to your projects.
If the organization you are applying to has a hiring manager from a non-data science background then understanding a portfolio with just images and link to your code can be discouraging ,to find your portfolio compelling you have to concisely explain what your project entails ,state the problem statement and how you were able to handle the problem, what tools and technology used so the hiring manager can fully understand the steps taken and the outcome of the project.
Conclusion Hiring managers are constantly on the lookout for fresh ideas and talents and having a portfolio that shines put you above your competitors. Your portfolio might not be a full website as a beginner. You may just need a section on GitHub.com or that one-page website on a free hosting platform that could showcase your data science projects.