Teaching

2023

CS4804: Introduction to Artificial Intelligence. Fall 2023 Syllabus

CS5804: Introduction to Artificial Intelligence. Fall 2023 Syllabus

CS5804: Introduction to Artificial Intelligence. Spring 2023 Syllabus | Student Project Showcases

2022

CS4804: Introduction to Artificial Intelligence. Fall 2022 Syllabus

CS5804: Introduction to Artificial Intelligence. Spring 2022 Syllabus | Student Project Showcases

2021

CS4804: Introduction to Artificial Intelligence. Fall 2021 Syllabus

CS4604: Introduction to Database Management Systems. Spring 2021 Syllabus

2020

CS4804: Introduction to Artificial Intelligence. Fall 2020 Syllabus

2017-2018

_{Amazon Web Services (AWS) essentials and architecting for Data Analytics (Part 1)}

        _{This course provides an introduction to AWS and offers a broad overview of terminology and concepts. The course will focus on the AWS web console, CLI tools, and data storage needed to be successful in data management on AWS. This course is intended as a prerequisite for the companion NLI course, Data Analytics using Amazon Web Services (AWS).
        This course will first give a broad overview of AWS terminology while giving a tour of the AWS web console. We will talk about users and user permissions and introduce the concept of least privilege. We will introduce the AWS CLI tools, and give an overview of what they can be used for. Then we will learn how to use these tools to do basic tasks like storing data and giving a user access to that data.}

_{Data Analytics using Amazon Web Services (AWS) (Part 2)}

        _{This course builds on the earlier course "Amazon Web Services‎ (AWS) essentials and architecting for Data Analytics." This course provides an overview of Amazon Web Services (AWS) services that can help you perform data analytics for your research in the AWS ecosystem. The course instructor who has received AWS Instructor-led training and AWS certifications will teach you how to use advanced AWS services, such as Amazon EMR, Amazon Redshift, and Amazon Kinesis. The course includes a combination of lectures and hands-on labs that expose students to these techniques.
        You will learn about creating big data environments, choosing appropriate AWS data storage options, working with Amazon RDS, Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, etc. and leveraging best practices to architect workflows to process research dataset and retrieve results in a cost-effectiveness way. This course is intended for faculty and students who are interested in learning about the advanced AWS services for performing data analytics in the cloud environment.}

Committee Member

• _{2023: Master, Chongyu He}

Honors College Coursework

• _{2022: Undergraduate, Lennon Headlee}

Undergraduate Independent Study

• _{2022: Undergraduate, Sid Pothineni}

Undergraduate Research

• _{2021: Undergraduate, Chongyu He}
• _{2021: Undergraduate, Paranav Sharma}

Teaching certifications

• _{Virginia Tech - Future Professoriate Certificate}
• _{Virginia Tech - TLOS: Professional Development Network (PDN) Instructors}
• _{Virginia Tech - TLOS: Professional Development Network (PDN) Advanced Instructor}
• _{Virginia Tech - TLOS: Professional Development Network (PDN) Master Instructor}