Not everybody in data science wants to work full time job with it. Further, there’s other ways to make money besides just working a full-time job at a company. In this articles, I intend to show you what other opportunities exist for data science professionals.
1. Do Freelance Work
1) Freelancing: With knowledge of data science, you could make a side income by doing freelance work. Upwork is the most popular spot on the internet for people who freelance. On this platform, you can encounter a treasure trove of thousands of projects to do for people. It’s very difficult to make a living as a data science who does freelance jobs for people/companies on upwork. After you successfully do a some projects and earn some excellent reviews, you would more easily get new projects to do. To begin, you must register an account on upwork. Other freelancing platforms were mentioned recently by Kurtis Pykes in the following: The Best Platforms To Land Freelance Data Science Gigs.
2. Produce Your Own Ebook
With the knowledge you have about data science, you could make an ebook to introduce people to data science. Making and publishing your ebook in this day and age is so simple and easy to do. There are tons of publishers out there who would be happy to publish your ebook for free. One such place to get your ebook published for free is Amazon Kindle Direct Publisher.
3. Make Vlogs
A video log or video blog, usually shortened to just vlog, is a type of blog which uses video as the medium, and is a type of web tv. You can produce short informational videos to educate people on how to do stuff in data science and post your blogs to YouTube. With popularity, these vlogs can generating an income via the YouTube partner program. The income is generated based on how many views you have and how many subscribers you have on your channel.
4. Make online courses for students
Producing courses on the internet is a big investment of time up front; however, once you make and publish the course, then it can be a good, income source. If you make an online course, it would be good to think about producing it as a massive open online course (MOOC), where a site hosts the course for you. The most widely used places on the internet for doing MOOCs include these places:
a) Coursera: https://www.coursera.org/
b) Udemy: https://www.udemy.com/
c) edx: https://www.edx.org/
d) DataCamp: https://www.datacamp.com/
e) Udacity: https://www.udacity.com/
f) Lynda: https://www.lynda.com/
You must read up on each website to know the guidelines for creating online courses with them. A course must be created per their rules.
5. Compete on Kaggle
One of the main reasons for joining Kaggle is to meet other professionals in data science; however, you can also participate in challenges on the site. By participating in challenges, you have the potential to earn money.