Network data is increasingly prevalent in scientific research and statistical inference, figuring prominently in such diverse fields as neuroscience, sociology, and public health, to name a few. In this course, we will investigate recent advances in statistical inference on network data. We will discuss the development of progressively more nuanced statistical models for networks, focusing on the recent advances in developing classical inference tasks within a network framework (e.g., hypothesis testing, clustering, classification, etc.).

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL).

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL).

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL).

This course provides an introduction to business intelligence and analytics, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data models and data retrieval, thus this course will review logical data models for both relational database systems and data warehouses. Students will learn to extract and manipulate data from these systems using Structured Query Language (SQL).

This course is designed to help students develop their skills relative to alternative music education experiences (other than traditional band, orchestra, and choir) for school and community settings. Emphasis will be on music making utilizing non-traditional instruments, with additional creative opportunities provided.