Xinjie Lan

In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: DSCI 435, DSCI 535, COMP 549. Mutually Exclusive: Cannot register for COMP 449 if student has credit for COMP 549/COMP 559/DSCI 535. Repeatable for Credit.

In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: DSCI 535. Mutually Exclusive: Cannot register for COMP 549 if student has credit for COMP 449/DSCI 435. Repeatable for Credit.

This course is an advanced machine learning course that focuses on the statistical foundations of generative AI in the Data Science (DSCI) Minor Program. In this course, students will study the fundamental concepts of statistics and understand the evolution of machine learning from discriminative to generative models. Specifically, students will learn two main foundation models: Transformers and diffusion models, via understanding their statistical foundations, comparing their advantages to classical models, and implementing the two models in real-world applications. Cross-list: STAT 420, STAT 626.

In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: DSCI 535, COMP 449, COMP 549. Mutually Exclusive: Cannot register for DSCI 435 if student has credit for COMP 549/DSCI 535. Repeatable for Credit.

In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: COMP 549. Mutually Exclusive: Cannot register for DSCI 535 if student has credit for COMP 449/DSCI 435. Repeatable for Credit.

This course is an advanced machine learning course that focuses on the statistical foundations of generative AI in the Data Science (DSCI) Minor Program. In this course, students will study the fundamental concepts of statistics and understand the evolution of machine learning from discriminative to generative models. Specifically, students will learn two main foundation models: Transformers and diffusion models, via understanding their statistical foundations, comparing their advantages to classical models, and implementing the two models in real-world applications. Cross-list: DSCI 420, STAT 626.

This course provides 1-3 credit hours of credit for STAT majors who wish to pursue a research project of mutual interest to the student and a faculty member in a selected area of statistical specialization. The student will conduct independent research under the faculty member’s direction. Repeatable for Credit.

This course is an advanced machine learning course that focuses on the statistical foundations of generative AI in the Data Science (DSCI) Minor Program. In this course, students will study the fundamental concepts of statistics and understand the evolution of machine learning from discriminative to generative models. Specifically, students will learn two main foundation models: Transformers and diffusion models, via understanding their statistical foundations, comparing their advantages to classical models, and implementing the two models in real-world applications. Cross-list: DSCI 420, STAT 420.