Best Data Science platforms to build your work portfolio in 2022!
While applying for jobs in today’s time, it’s quite common, rather obvious to have a professional CV mentioning a set of qualifications, skill sets and work experience one possesses.
Undeniably, CVs play a very important role at forming an impression on a potential employer at its first glance. However, a CV in itself is not enough to help you land your dream job, what you need alongwith with your CV is a portfolio! Especially if you’re from a technological background.
As a part of our job at SDBI, we mentor students and assist them with getting placements after their degree is completed at our institute. Something we always suggest is to have a portfolio that showcases your work at its best and makes it easy for the employer to understand your skills sets and strengths for the offered job role. It ultimately also leaves a very good impression on the employer.
Bringing to you our today’s topic of discussion – Best Data Science platforms to build your work portfolio in 2022!
Being from a technological background like Data Science, Portfolios are your best friend, when applying for jobs. In this blog, we have accumulated our best understanding on the platforms that not only help you get hands on with Data Science concepts but also provide you with a wide space to showcase your work and make a portfolio.
Being in the technological domain, you must have already heard about Gitshub (A Collaboration on Software Development). In 2019, a similar platform called DagsHub was launched specifically as a Data Science and Machine learning community.
Its an increasingly developing platform for data scientists and machine learning engineers to come together at a common ground to build their work.
As per the founders, DagsHub is a home for open source data science, where everyone can contribute and make research and development process transparent.
It’s one of the best platforms to work with large or changing data for your project. All you have to do is sign up, consolidate and collaborate.
Kaggle would definitely be on the top of our list!
It is an online association of data scientists and machine training practitioners. Kaggle permits users to find and issue data sets, investigate and develop models in a web based data science background and work behind other data scientists (a great way to getting good exposure).
The best part is you can participate and host competitions to test your data science skills(a good point to add in your cv).
All you have to do is choose a programming language (our recommendation would be python), study basics of transversing data, learn about machine learning model and try kaggle competitions.
Data Camp –
A platform especially designed for students!
Datacamp allows you to learn and practice your data science skills from non coding essentials to data science and machine learning.
You can take their assessment and discover your Data Science skill level (an ideal way to improve your skills). You can get access to DataCamp’s workspace, wherein, you can write code, analyze data and share your data insights. With their ready to use data sets you go from learner of data science to a practitioner of data science.
It’s a highly suggested platform for building your Data Science portfolio! It allows you to share and collaborate on your work.
Simplest of all, yet the most impactful in today’s time. YouTube as a platform has reached boundaries in every domain possible, leaving data science as no exception! You can learn and showcase your work at the same. Sometimes you might even end up finding great ideas for your new projects. Infact, showcasing your work through your blog or YouTube can be one of the best ways to make your portfolio stand out.
These were our top picks to make your portfolio stand out and help you get that dream data science job. Before we put an end to today’s topic, we’d like to give you a small tip. Inculcate more of real life project ideas for your portfolio, that would help the employer to judge your capabilities parallely with the required job profile.
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