SDS 128: Confident Data Skills

Welcome ladies and gentlemen to the SuperDataScience podcast. And today I have a super exciting announcement for you. For the past one and a half years, since July 2016, I have been working on a very, very interesting project. I have been writing a book. Yes, it’s taken a long time. I was not expecting how long it would take. I was approached back then, in 2016, by a publisher who suggested that it would be a pretty cool idea to write a book. And at the start, I was actually thinking that this sounds like a lot of effort, and I was about to say no. To be honest, I was very close to saying no. I was thinking about it for a few days. But then I thought there were already the courses, there was already – what else did we have at the time? The podcast was just kicking off then, and there was a lot of different content. There was the blog and other sources of information where I was sharing data science. And then I thought, why not add a book to all of that. I know it will be a lot of effort, but let’s give it a shot.

And it took one and a half years and today I’m finally super excited to announce that the book is live. You can get it on Amazon, you can get it on amazon.co.uk, you can get it on amazon.com, you can get it in your local bookstore. If you’re in a big city then you definitely can. The book title is “Confident Data Skills”. So what is “Confident Data Skills” all about? Well, I looked around the world at the time of starting this project and checked out the different types of books there are. And definitely there are some very interesting books. There are some books that are very respectable, such as a book by Nate Silver, “The Signal and the Noise”. There are some more technical books, which a lot of our guests have recommended on the podcast. There are some books on visualisation, some books on storytelling. Lots of different types and varieties of books.

But in this book, what I wanted to do is I wanted to combine all of the steps involved in the data science journey, but also not make it a coding book. So that’s what I wanted to steer away from. So I wanted to make it a book that you could actually just read. You didn’t have to sit in front of a computer and code. Because to be honest, there’s lots and lots of other sources where you can get the coding skills and examples. What I wanted to create was a book which you can sit down on the train and read. And more importantly, I wanted to create a book that’s pretty much for anybody, anybody wanting to break into the space of data science. Or somebody who’s already in the space of data science. Or even somebody who is an expert in the space of data science. A book that would unite all of us and give the best practices, give the tips and hacks, and give the intuition behind the things we do, outline the data science process step by step, and make it fun.

So I tried to make it as personable as possible so that you can follow along and see my experiences, and also see a lot of experiences of the guests on the podcast and industry experts. So there’s lots of case studies in the book and lots of personal stories as well. I think it does a good job combining the whole notion of data science, but also making it light. I’ll share this with you. I’ve been reading the reviews on Amazon, because it just went live on Amazon just a few days ago. People have already been submitting reviews and right now there’s 27 reviews and I’ve read every single one of them. I’m very excited to hear that people find it a light read. People find it non heavy, non consuming. It’s actually as I wanted it to be. I think it reads like in between a novel or a story and the actual data science. So it doesn’t scare away, even if you’re just starting onto the space of data science, it shows you that it actually is possible to build a career for yourself and it’s not that difficult at all.

So that’s what the book’s all about. There’s lots of surprises, and if you’ve been listening to the podcast, there’s lots of cameo appearances by guests and you’ll hear different stories. I won’t give away all the secrets now, but there’s lots of stories from our guests that pop up in the book. And some very interesting examples that haven’t come up before. What I wanted to say as well was where you can get the book. You can get it on Amazon, so you can go directly there and just search for “Confident Data Skills”. If you want to get some additional bonuses, then we’ve set up a website, www.confidentdataskills.com, one word. You can go there and, depending on how many books you want to get, even if you get one, you still get a bonus with your book. Even if you already purchased it, you can still go there and just apply for that bonus and it will be sent to you. So that is just an extra way for us to say thank you, plus I have some additional information about the book there.

And what I wanted to say is if you have gotten the book, if you have some time, please submit a review on Amazon. It would really, really help us out to get the word out there. Our goal is to make this book as popular as possible and hopefully, my dream right now is to hit the Bestseller level on Amazon, and that requires of course people checking out the book, people buying the book, and of course submitting reviews.

So if you have submitted a review, if you’re one of those 27 people that I’ve seen reviews already, then thank you so much. If you haven’t yet, I would really appreciate if you could help us out that way. Right now, I’m reading all the reviews as they come in, but I’ll aim to keep doing that for as long as I possibly can, and I would really be interested to hear what you have to say about the book. And just submit an honest review. Whatever you think it is, how many stars you think, just press that button. I welcome any level of reviews, that would be great.

And let your friends, colleagues, or family know about the book, about the site confidentdataskills.com. The more people can get on board, the better. I really think this book can help people break into the space of data science and that’s all. Thank you so much for checking out this podcast. I hope you’ll check out the book. And I look forward to seeing you back here next time. Until then, happy analyzing.