Working hands-on is what makes you a data scientist. Let's get you started the right way!
Master the Data Science Method is a project course. The structure of the course follows data science project phases. As you go through the course, you learn key data science concepts and observe how a data scientist works but also build a project of your own. At the end of the course, you will have a portfolio-worthy project to share with the world, already on your GitHub account, all ready to present!
“I am currently taking a much longer, pricier DA bootcamp... Nowhere have they laid out a simple best practice outline for my notebooks as you have here. So much of the value you're providing is simply letting us into the mindset and process flow of an experienced data scientist - thank you.”
“What a great course! I recommend it to anyone who wants to experience what activities you need to perform and how you need to think as a data scientist.”
“This course is really one of a kind. I like the fact that Mısra appears in all the videos. It created a
kind of teacher-student environment that helped me throughout the course.”
“This course is an incredible opportunity for aspiring data scientists to learn through a real-world hands-on project.”
“This course is awesome because it gives me a complete guide to a data science project from start to finish. The explanation in each module is quite clear and easy to understand.”
Get your first project done fast!
You keep hearing that you need a portfolio to apply for data science jobs. In this course, apart from learning about new concepts, we will build a portfolio-worthy data science project.
So you can improve your skills and have something to show for it!
All the results, without the hassle of trying to figure everything out yourself!
In this course we cover the complete data science pipeline.
Assignments to get you hands on
Video walk through of expert solutions
PDF explanation of key concepts
I will walk you through my code, explaining my decisions and talking about how I decide on the next steps.
All videos come with machine generated subtitles.
On top of the course videos, you will get access to short explanation documents. These will support your learning and make sure you understand everything I use in my code.
With the course, you get a whole repository including all the code from the course. You can use this to follow along, or as a reference for when you get stuck.
You can of course learn every bit about building a data science project yourself, but this will take significant amount of time and energy. Moreover, some problems in data science are very subtle. You might not even realise that you made a mistake until someone points it out.
Let me help you get started the right way!
*Click on the lessons with bold names to preview them for free!
Hey I am Mısra,
I am a data scientist by day and online creator by night. Currently I work for a pharma-tech company called myTomorrows in Amsterdam, the Netherlands. Before that I worked as a data scientist at IBM.
Apart from my data science work, I like teaching people what I know. I always received lots of questions on LinkedIn about my career and data science in general from people who wanted to end up where I am. That's why I started So you want to be a data scientist? That's where I share my knowledge and experience through my articles and access to my connections through my podcast.
I made this course after I realised that the biggest deficiency of aspiring data scientists is practical experience. I designed it to help you bring together all the little bits of knowledge you acquired so far in order to build a project you can be proud of.
The course is designed to teach the most through hands-on learning. If you don't know Python, you can still learn the concepts and the general data science project structure but you will not be able to implement your own project.
In other words, it's up to you and will depend on what you want to get out of this course.
You do not need to be a Python guru. The base requirement is that you need to know how to read and understand code in Python.
No. We will start from scratch. I will guide you through setting up everything you need to complete this course.
This will depend on the amount of effort you are willing to give to the course. I expect it to take 2-3 weeks to finish assuming you can spend 10+ hours on it per week.
The course is OS agnostic except for the data science environment set-up. I demonstrate the installation of Git and Anaconda on MacOS. The rest of the course is suitable for users of any operating system.
I will add the Windows instructions of data science environment set-up in the next version of the course.
Yes. This course comes with a 30-day money back guarantee. If for any reason the course does not meet your expectations and you would like a refund, send me an email at email@example.com and I will arrange your refund.
Start with my free course.