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John M. Olin Library, Instruction Room 3

Introduction to Machine Learning (Session 4)

This four-course seminar will provide participants with a basic foundation in Machine Learning. Machine Learning is a rapidly growing field of interest and is a valuable skill for a data-oriented researcher in any domain. The course will begin with an exploration of Python environments and how to set them up. Following this, we will delve into the realm of datasets, learning about their role in machine learning. Practical applications will involve hands-on experience with the Pandas library for data manipulation, basic data analysis, and visualization techniques. The focus will then shift to understanding basics of machine learning tasks and implementing models in Python using the Scikit-Learn library. By the end of the session, participants will gain proficiency in integrating datasets into an ML training pipeline and training simple machine learning models in Python.

This course is open to graduate students, faculty and staff from any field at WashU who are interested in learning about machine learning. Participants are expected to have a basic proficiency in Python (taking the Introduction to Python training series should be sufficient and some familiarity with data in tabular format).

This class will be fully in-person, and participants will use their own laptops. Enrollment is limited to 20.

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DataLab Workshops 

DataLab is a collaboration between Data Services and TRIADS, Bernard Becker Medical Library, TechDen, and DI2 to provide a breadth of workshops from the basics of understanding data to working with data tools. These workshops are open to all WashU affiliates and are held in the fall and spring semesters.