 In this video, I'm going to explain to you five different ways that you can earn some passive income as a data scientist. Let's get into it. In reality, no income is truly passive, but what we mean when we refer to passive income is income that you get that is not directly tied to your time. For example, buying a property and renting it out is a form of passive income. It does take initial work and capital to buy the property. However, after you've bought it, you'll then get rent and monthly cadence normally with no extra work needed on your part. It's also important to mention that all these things I'll discuss in this video aren't get rich quick schemes and it takes a while to get off the ground. Blogging is one of the oldest ways that you can make money on the internet. Traditionally, blogs get paid, put a number of views they get by advertisers. You can expect to get anywhere between a few cents to a few dollars per thousand views on your blog. This is actually quite difficult and you need a lot of views to make any substantial income, particularly if you want to earn a full-time living. The other hard part of writing your own blog on your own website is that you need to rank high on Google searches, which is quite hard to do. This is why, if you're a beginner, I highly recommend platforms like Medium, which have an in-built recommendation system and distribution system. You can also submit your articles to publications, which will then distribute your content to their audience. From experience, Medium pays roughly a dollar to five dollars four thousand views, but this is heavily dependent on other statistics, such as claps, comments, and read time. The Pi Coach, who is the biggest tech and data science writer on Medium, earned roughly 10k a month in 2022. That is a lot of money to get, just from simply writing data science and Python tutorials, so there's no reason why you can't do the same. Even if you don't own millions, you'll still develop the useful skill of writing. Ryan Peterman, who is a staff software engineer at Instagram and has over 40,000 subscribers to his newsletter Developing Dev, said that, the better you are at writing, the better you will be at building software. The same is true for data scientists. Being a better writer means you improve your thinking, and improving your thinking means that you can solve more complex problems and have more innovative solutions. This is something that is so useful for data scientists, and will be an invaluable skill in your career. Newsletters are relatively old concept, however, they've been making a big comeback recently. Newsletters don't necessarily have to be news, they can be more like blog posts. In fact, most newsletters nowadays are like blog posts, which you just distribute out to your audience at a specific time at a certain cadence. Jordan Cutlett, high-growth engineer newsletter, went from zero to 36,000 subscribers in just nine months, earning him $5,000. But that is just the tip of the iceberg. George Lee, Oroch's newsletter, pragmatic engineer earned him $62,000 in his first month of writing in September 2021. It is now estimated that he's earning over $1.5 million before feet from this newsletter alone. Obviously, George Lee, Oroch's newsletter is an outlier, but it does go to show you that writing a newsletter can be very profitable. These two writers that I've just discussed mainly write about guidance and advice in tech, things such as how to write tech reviews and how to get promoted. This is something data scientists can do equally as well. If you are a senior data scientist especially, I'm sure people will love to hear how you went about from becoming a junior to a mid-level to a senior and the skills you needed at each step. This is just knowledge that you already know and you can just share publicly online and potentially have a really good newsletter like these other writers I have just mentioned. There are many ways to monetize a newsletter. The first one is simply just to have a paying newsletter, so people can only access your emails if they pay a certain fee. However, I don't recommend this system unless you have an existing audience because if you're a beginner, no one's really going to give you their money because they don't know who you are and they don't really know how valuable your information really is. The second way, which is like a hybrid system, is that most of your newsletter or content is free. However, you have a paid tier where subscribers can pay a bit of money to have access to exclusive content that you will give to them. You can also go to the other end of the spectrum where you have a completely free newsletter and simply rely on sponsorships and ads to generate your income. This is exactly what Ali Abdel's Sunday Snippers newsletter does and he makes roughly a few thousand dollars per email. If you want to start your own newsletter, I highly recommend you use Substack as your platform. I use it. I love writers. I've mentioned this video. Use it and it's very simple to start with. A YouTube channel is arguably harder to grow than a blog. However, the long-term rewards often can be higher, but you really are in it for the long haul. To start monetizing your YouTube channel, you need at least a thousand subscribers and 4,000 watch hours. According to a study done by TubeBuddy in 2021, it takes the average person 152 videos to reach a thousand subscribers. That's a lot of time making content, scripting, editing videos or a little reward to show for it. The average CPM, which is how much you can expect to get earned for a thousand views, varies a lot between a few cents to a few dollars, which really depends on the niche you're in. Typically finance videos will have a higher CPM and entertainment videos have a lower CPM. Tech is normally the higher end but not as high as finance. There are many data science YouTube channels out there such as CodeBasics, Ken G and Corey Schaefer. There are also newer channels such as ModeChen and DataNash who have only been posting for a couple of years but are doing very well on the platform. According to SocialBlade, CodeBasics makes anywhere between $312 to $6,000 per month from the YouTube channel purely on ad revenue from Google AdSense. All this goes to show that a YouTube channel can be quite lucrative but it does take a lot of time to get off the ground. If you don't want to make videos but don't mind speaking to a microphone, then a podcast is your best bet. There are many data science podcasts out there such as child time data science, data skeptic and data science at home. There is also a lot of room to grow in this area. Just look at Lex Freeman. He started his podcast in 2018 and he now has over 3.5 million subscribers on YouTube. There are many free platforms out there to host your podcast such as Acast, Podbean and Spotify and they vary in how they monetize your podcast. So it's best to do your own research and pick the one that suits your needs the most. A common ballpark of how much you can earn from a podcast is roughly $20 for a thousand downloads and another way you earn money is through ads. So an advertiser will typically pay $25 for a 60-second ad per thousand listens. Growing a podcast is generally harder than growing a YouTube channel mainly because the distribution system and recommendation engine is just not as advanced on these platforms as it is on YouTube. This is why a lot of podcasters have an associated YouTube channel to help drive traffic. As data scientist, we have a lot of skills. Maths, statistics, Python, SQL. So why not take all that knowledge you have, wrap up into a course and sell it online. Perhaps the best example of someone selling the skills they already know online is Kat Norton aka MsXL. She's estimated to make $100,000 per day from her Excel courses. There are so many platforms out there to create your course, Skillshare, Teachable, Udemy, and they make it so easy to make it and you don't have to worry about the maintenance or infrastructure costs it may have to host your own course on your own website. The hardest part of a course is distribution and marketing, particularly if you don't have an audience it might be very hard to sell your course. If I had to rank these five passive income ideas I've discussed in terms of which one I think you should begin with, particularly if you're a beginner, then I'll say definitely start with a blog or newsletter first, only because the upfront cost is so little or you need a laptop to get going and there are platforms such as Medium and Substack which make it very very easy to start. The next two hardest in my opinion would be a YouTube or the podcast, only because you need a microphone or camera to begin with to make sure they're high quality enough that you may get some traffic. And finally the online course is something I will leave to last unless you're really keen on doing this because it's very hard to sell an online course with no audience. But as I said throughout this whole video don't do these things purely for the money, do them because you want to share and also learn more things. Along the way you'll develop useful skills and maybe earn some income but everything you will learn will make you a much better data scientist overall. If you enjoyed this video and want to see more content like this then click the like and subscribe button and I'll see you in the next one.