What decisions is it safe to leave to the new Machine Learning algorithms?What questions do you need to ask your data science lead? How should your humans be providing machine oversight?

AI is rarely about replacing humans at the moment - it's about augmenting them. We know that looking at the world mathematically can give you a different view on the work that you do, but with machine learning, the rules have fundamentally changed. In this course, we talk you through how machines make decisions on your behalf and the many compromises that they have to make. We provide insight into where the machines might excel, and times when they really should not be trusted. Team-based work is about to get more difficult, now that there's a machine on the decision-making team. On this course, we welcome you into this new world of machine thinking with practical examples and applications throughout.

Course contents:

Introduction

1. When human thinking lets you down - the many fallacies humans fall prey to

2. Machine vs Man - what the machines bring to the work place

3. Linking - how linking makes the magic happen

4. Search and speed - the benefits and limitations of scale

5. Leveraging memory - creating and accessing machine memory

6. Tough choices- the world of compromises

7. Breaking a problem into parts - how computer vision works and sometimes doesn't work

8. Errors in the data collection - garbage in, garbage out

9. Cause and effect - where the machines fail

10. The third way - contracting 3rd party software