Hi and welcome to this introduction to machine learning and data science course. My name is Jordan Hudgens and I'm going to be your instructor throughout the course material.

Our first stop on our journey on learning about machine learning and data science is to look at the parent technology which is artificial intelligence.

Now that you have a high-level understanding on what Artificial Intelligence is let's take a step back and compare the differences between artificial intelligence machine learning, data science, and big data because those are terms that some people use interchangeably.

Products and technologies that use artificial intelligence are all around us. We're using them every single day whether we realize it or not. And in this guide, I want to walk through some of the basic examples of AI agents that are out there to help give us a frame of reference for how AI can be used.

So far in this section, we've been talking about the broad ecosystem of artificial intelligence and in this guide. I want to narrow our focus just to machine learning.

So now that you're familiar with what machine learning is and we've walked through our first high-level case study, let's talk about what data science is.

With our understanding of artificial intelligence machine learning and data science fresh in our mind. I want to take a step back in this guide and I want to get very practical.

Extending on the topic of practical approaches to machine learning in this guide we're going to discuss three potential architectures that you can use when you're building out your own machine learning programs.

We've come to the end of Section 1 and now it's time for our first piece of homework in the course. And what you are going to be asked to do is to write a paper or if you're not a fan of writing then film yourself giving a screencast and the topic is I want you to pick out your own case study.