Data Science Inside a Modern Data Science Curriculum

If you're thinking data science, here's exactly why the curriculum is structured the way it is. For more career advice, make sure you follow. One of the biggest mistakes beginners make is wanting to jump straight into AI right foundation, copying code without understanding what's happening. And that's why the curriculum starts with Python and object oriented programming. Before you can analyse the data, machine learning model, you first need to learn how and efficient code. And once you've got the foundation, into Pandas, Numpy, Macropod lib and Seaborn. This is where the data science really begin. You will learn how to clean messy data sets, analyse the information and create visualisations to uncover insights. Then comes something that a lot of people try to avoid. Linear algebra and statistics aren't there to make the course harder. They're there to help you understand how machine learning models actually work, not just a black box. At the same time, you learn sequel so that you can understand how to retrieve data from databases and get help so that you can manage your code like a professional developer only. Only then the curriculum moves into machine learning where you learn everything from regression and classification. But what I like most about this curriculum is not what you're learning, it's how you're learning it instead. Instead of working on any random data sets, you're working on actual real world data sets throughout the bootcamp. This will allow you to feel how it is to be in a data role in a real world job. And then you're also not learning on your own. Throughout the bootcamp, you'll have access to experienced tutors, life support and a community of learners that will help you when you get stuck. This is important because data science is challenging. To learn alongside makes a big difference. And then towards the end, the entire focus changes into getting you job ready. This basically means building a strong, developing a portfolio of projects and making sure you have real work that you can show your employer, not just a certificate. Because at the end of the day, the goal is not to learn just data science, it's to be ready to start a career in it. If you're on more details about this program, the link is feel free to comment section below. And for more career advice, make sure you follow.