CIS 8045 Unstructured Data Management (Graduate level), Instructor, Fall 2024
This course addresses the unstructured data management skills needed for modern data analysis, including those salient to big data, real-time data environments, and AI-driven analytics. The focus is on unstructured data and its environment. Unstructured data includes web data (blogs, text), user-generated content (UGC), social media, location-aware data, and digital media, among others. Students will learn how to transform text into mathematical forms using Natural Language Processing (NLP), analyze images through AI-based image processing techniques, and employ NoSQL (Not Only SQL) databases to manage unstructured data. The course will also cover how AI algorithms can be applied to extract meaningful patterns and insights from unstructured data sources, enhancing decision-making processes.
INFO 3237 Business Analytics II (Undergraduate level), Instructor, Fall 2020-Fall 2023, Syllabus
This course's primary goal is to equip students with the proficiency to comprehend, dissect, and interpret business scenarios through data analysis. The course is strategically structured to impart highly sought-after business analytics competencies that are in high demand within the job market. The curriculum’s core focus revolves around analytic skills in predictive analytics, encompassing an in-depth exploration and application of various machine learning models such as random forest, text analysis and cluster analysis. Hands-on experience with practical tools like Python and R.
DSBA/MBAD 6211 Advanced Business Analytics (Graduate level), Instructor, Spring 2021, 2022, 2023, Syllabus
This course is designed to help students apply advanced business analytics techniques to explore and analyze various data types, so they can find subtle and non-trivial relationships that are understandable, useful, and executable to business owners. Managers in various functional areas can exploit valuable insights gained via fact-based decision-making to achieve competitive advantages. Hands-on experience with practical tools like Python and R.
MIS855 Data Science (Undergraduate level), Instructor, Spring 2018
MIS855 Data Science (Undergraduate level), Teaching Assistant, Fall 2017
Data Mining and Predictive Analytics (Graduate Level), Teaching Assistant, Fall 2014
Data Models and Decisions (Graduate Level), Teaching Assistant, Spring 2014