Prerequisite: Basic BI and data analysis knowledge; statistics 101
The power behind self-driving cars, real-time facial recognition, and intelligent robots is called machine learning,a subfield of artificial intelligence (AI).The first formal definition of AI came from Arthur Samuel in 1959: “A field of study that gives computers the ability to learn without being explicitly programmed.”They’ve learned an awful lot since then.
Currently, machine learning not only enablescomputers to park our cars and win at Jeopardy, it also allows them to beat humans at chess and Go, and to learn for itself how to play new games without any instruction.Although these are all very flashy applications of this technology, the business applicability has so far been limited. Nevertheless, understanding how machine learning algorithms work can be very useful in a business context. This can also lead to potential applications in sales, marketing, finance, and HR that can drive better decisions and give you a competitive edge.
You Will Learn
- What machine learning is and why it should be part of your analytics toolkit
- How the most widely used algorithms work and how to apply them
- Best practices and use cases in applying machine learning techniques
- How to start applying machine learning algorithms in an automated decisioning framework
- BI managers and analysts, information and business analysts