ONST-ML-ANALOG - Machine Learning Basics for Analog

Program Overview

This course introduces the concepts and techniques of machine learning for transforming raw data into business intelligence and insight. It is intended to provide the participants with the working knowledge for using and developing machine learning technologies. The course studies how data-oriented machine learning techniques can be used by organizations to gain competitive advantages. The course will cover machine learning methodologies and demonstrate examples using an interactive software tool that does not require any programming knowledge. Use of machine learning models and applications from end user perspective will be emphasized. Topics include data integration, data transformation, classification, prediction, clustering, and association analysis. Machine learning related organizational issues will also be discussed.

Course Outline

The objective of this course is to provide students with key concepts and terminology in machine learning with emphasis on business applications. At the conclusion of the course, participants will be able to:

1. Explain key steps in a machine learning process
2. Analyze a business context to assess potential machine learning opportunities and implementation strategies.
3. Set up a business analytics project for analysis using machine learning concepts
4. Explore and describe a given dataset related to a problem context using descriptive statistics and data visualization techniques
5. Describe key concepts and underlying intuitive rationale for commonly used machine learning techniques
6. Compare and assess model performance in the context of a business problem resulting from application of machine learning techniques
7. Discuss integration of machine learning with organization strategy

Learner Outcomes