Introduction to Machine Learning

This mini course will explain what is machine learning and illustrates how machine learning is used in Inventory Management and Predictive Analysis; Assets Management and Risk; Informational Retrieval, Advertising Targeting, Product Pricing, and will explain machine learning algorithms.

What am I going to get from this course?

Define Machine Learning and give a brief history of Machine Learning.
Define Data including Data Types, Data Dimensions, and Data Classifications in terms of Computer Programming and apply this knowledge in classifying their own data.
Define Algorithm including the various types of Algorithms and the Logic using in Computer Programming and apply these concepts to writing their own algorithms.
Understand what a Protocol is for, name the types of
Protocols used by computer networks, the different types of networks including the Internet and World Wide Web.
Understand the underlying numeral systems used in machine languages and the various levels of programming languages.
Understand how Machine Learning applies to Inventory Management, Assets Management and Risk Analysis and how Machine Learning applies to their business and personal finance.

Prerequisites and Target Audience

What will students need to know or do before starting this course?

There is no required materials or software for this course.

Who should take this course? Who should not?

As an introduction to Machine Learning, this course is presented at a level that is readily understood by all individuals interested in Machine Learning. This course provides a history of Machine Learning, defines data and explains what is meant by big data; and classifies data in terms of computer programming. It covers the basic concept of numeral systems and the common numeral systems used by computer hardware to establish programming languages. Providing practical applications of Machine Learning.