Providing Technology Training and Mentoring For Modern Technology Adoption
Machine Learning is the process of discovering interesting knowledge from large amounts of data. It is an interdisciplinary field with contributions from many areas, such as statistics, artificial intelligence, information retrieval, pattern recognition and bioinformatics. Machine learning for predictive analytics is widely used in many domains, such as retail, finance, telecommunication and social media.
This course provides an overview of various machine learning techniques with examples of how they are used in various organizations such as retail, finance, biotechnology and social media. Case studies are used to allow participants to work through several machine learning issues using the techniques described and to recognize opportunities within their organization.
Note: This course uses a visually oriented, open source software package to process the data. The class is not intended to be a programming class. Instead, the software is used to examine the impact of different data mining decisions.
Upon completion of this course you will be able to:
This course will be accessible to students without prior training in quantitative research methods. However, students with a background in basic descriptive and inferential statistics will, most likely, get more out of the course.