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Hi All! Hope all is well :) Have you ever thought about building experiences outside your student life or even your career for that matter to break into Data Science? I was reached by many students asking about data science careers and there is only one piece of advice I can give is to build your portfolio with projects that can boost your resume. However, it's easier said than done.
Below are 4 ways to showcase your data science skillset:
Simple projects:
There are several projects that can be as simple as Exploratory Data Analysis. Find a problem that is of your interest and develop an ML model based on the problem statements:
Some ML models types to focus on:
Exploratory Data Analysis
Regression
Classification
Recommendation Engine
Sentiment Analysis
Personal Projects (Advanced):
Based on your interests, you can start working on a personal project that can be fun. Building a project from data collection to hosting on a web app showcases your talent on the different steps in building ML/DL models as well as your ability to code project applications.
Some ideas:
Monitor fitness habits
Monitor finance
Fun projects using Youtube/Twitter/Spotify APIs
Chatbot project with NLP
Pop bandmates Face detection using Neural Network
Open Source Projects:
These projects are the best way for coders and developers to test their skills and showcase their talents. Working on open-source projects that are impactful and building the community can speak a thousand words about your contributions.
There are lots of open source projects (follow the below resources):
Ovio.org: The projects here are open source GitHub projects. On this site, developers can find a large portfolio of contributor-friendly projects ready for contribution.
First Timers Only: This site hosts open-source projects that are meant for new coders and developers. They have extensive resources on how to start your contribution towards open-source projects.
There is an article written by Sara A. Metwalli on the list of data science open-source projects you should mind contributing to.
Hackathons:
Are most application type and this is mostly within the short time frame. There are various hackathons that tackle real-world problems and build innovative solutions. Some of them may be student-oriented but some are for professionals as well.
Some of the resources:
BuildwithAI: There is one hackathon coming up for 2021, Oct 29 - Nov 2, 2021.
Angelhack.com: There is one Aisa Pacific, China Virtual hackathon coming up from Oct 22 to Dec 12, 2021. "THE POLKADOT HACKATHONS: APAC EDITION"
Hackathon.io: There are several hackathons coming up on this site ranging from sustainability to global business hackathons.
Analytics Vidhya: Most renowned website for hackathons, Analytics Vidhya hosts multiple hackathons at their site. The upcoming hackathon from McKinsey & Company is a deal-breaker.
These are few important ways to build Data Science Experiences outside the job and showcase your talent to employers with respect to real-world data science problems. Remember “Consistency is the Key” to work and improve on any challenge/skill.
That's all for this week. If you like this post, feel free to like, share, and subscribe to this weekly newsletter for weekly updates on Data Science related topics.
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