executive data science

EXECUTIVE DATA SCIENCE

Statistical Foundation, Application, Implementation, and Ethical Implication

Thurs, Oct 17 | GSU Buckhead Campus, Tower Place 200 | 7:30 AM - 4:00 PM

Location: Registration in Lobby | Breakfast in 1201 | Workshop in Room #406

principles

  fundamentals of statistics, machine learning and algorithms - along with emerging technologies

ethics

Learn how to think through the ethics surrounding privacy, data sharing, and algorithmic decision-making

application

Assemble the right team, ask the right questions, and overcome the challenges of data science implementation

OVERVIEW

Taught by a distinguished team of professors from Kennesaw State University's Analytics and Data Science Graduate Program, including the Associate Dean and Director of the Analytics and Data Science Institute, Dr. Jennifer Priestley, and the Director of the school's Center for Statistics and Analytics, Dr. Gene Ray.

Aimed at corporate leaders, business managers, and anyone considering a career in data science.  This workshop will also cover the fundamentals of statistics, machine learning and algorithms that are critical components to data science initiatives.

JPRIEST

JENNIFER PRIESTLEY, PHD

ASSISTANT DEAN, GRADUATE COLLEGE
KENNESAW STATE UNIVERSITY

Dr. Priestley is the Associate Dean of The Graduate College and the Director of the Analytics and Data Science Institute at Kennesaw State University. In 2012, the SAS Institute recognized Dr. Priestley as the 2012 Distinguished Statistics Professor of the Year. She served as the 2012 and 2015 Co-Chair of the National Analytics Conference. Datanami recognized Dr. Priestley as one of the top 12 “Data Scientists to Watch in 2016.”

Dr. Priestley received a Ph.D. from Georgia State, a MBA from The Pennsylvania State University, where she was president of the graduate student body, and a BS from Georgia Tech.

gene

HERMAN ' GENE' RAY, PHD

DIRECTOR, CENTER FOR STATISTICS + ANALYTICS
KENNESAW STATE UNIVERSITY

Dr. Herman Ray is an Associate Professor at Kennesaw State University, where he is the Director of the Center for Statistics and Analytical Research. He is actively involved in the data science community and works with many industry partners to solve problems. His research interests are in clinical trial design methodology as well as understanding the workforce responsible for STEM education in the secondary education system.

Before joining KSU, Dr. Ray was employed by Thomson Reuters in several different positions including Research Scientist. Herman received his B.S. and M.S. in Mathematics from Middle Tennessee State University and his Ph.D. from the University of Louisville.

AGENDA

7:30 AM - 4:00 PM

REGISTRATION + BREAKFAST

MORNING SESSION

Coffee Break Included in Each Session

8:00 – 9:15

·        Introduction to Concepts

·        Statistics Basics

·        Prediction/Classification/Patterns

·        Data Science vs Statistics

9:15 – 9:30

Table Talk – Dissecting Buzz Words

9:30 – 10:30

The role of:

·        Statistical distributions

·        Transformations  in pre-processing

·        Imputation Strategies

10:30-10:45

BREAK

10:45 – 12:00

·        Feature Engineering

·        Variable Reduction

·        Binning

LUNCH + NETWORKING

AFTERNOON SESSION

Coffee Break Included in Each Session

1:00 – 2:00

From Statistical Modeling to Machine Learning

·        Methods

·        Examples

·        Metrics

·        Pros/Cons

2:00 – 2:15

Table Talk – Analytics and Machine Learning Case Studies

2:15 – 2:30

BREAK

2:30 – 3:30

Ethical Considerations in Data Science

·        Human Subjects

·        Algorithmic Biases

3:30 – 3:45

Table Talk – Ethics Case Study

3:45 – 4:00

Summarization and Wrap Up