Undergraduate certificate Statistics and Machine Learning

SML 101 Reasoning with Data QR Data-driven decision-making, research discovery, and technology development are everywhere. It is now more important than ever for individuals to understand how data are used for these purposes. This course will introduce the student to how statistical reasoning and methods are used to learn from and leverage modern data. The emphasis will be on concepts and strategies for learning from data, rather than on sophisticated mathematics. Students will be exposed to the basics of statistics, machine learning, and data science through real world problems and applications. Students will also analyze data sets using the computer. Staff

SML 201 Introduction to Data Science QR This course provides an introduction to the burgeoning field of data science, which is primarily concerned with data-driven discovery and utilizing data as a research and technology development tool. We cover approaches and techniques for obtaining, organizing, exploring, and analyzing data, as well as creating tools based on data. Elements of statistics, machine learning, and statistical computing form the basis of the course content. We consider applications in the natural sciences, social sciences, and engineering. Staff

SML 302 Fundamentals of Machine Learning (See COS 424)

SML 310 Research Projects in Data Science Fall/Spring Project-based course in which students work individually or in small teams to tackle data science and ML problems based on real datasets. We will emphasize critical thinking about experiments and large dataset analysis along with the ability to clearly communicate one's research. This course is intended to support students in developing the analytical skills necessary for quantitative independent work; students should consult with their home department about how this course could appropriately complement, but not replace, their independent work requirements. Staff