Machine learning
Machine learning is an important branch of applied mathematics that is increasingly used in medicine and biomedical research. In this course, students will be introduced to fundamental algorithms used in machine learning systems beginning with the method of least squares, or Linear Regression, move onto a brief introduction to electronics and Quantum Mechanics, and then apply these to predict the systolic blood pressure of patients based on their age and weight. Student teams will choose a problem to study and use publicly available datasets to analyze the data using the methods learned in the course and identify opportunities for machine learning in health care settings.
Students will learn to:
• Define and explain uses of machine learning
• Apply one and two dimensional linear regressions
• Implement basic electronics to understand machine learning concepts.
Instructors: Michael Kumaresan, Cooper Union Alumni and Adjunct Faculty, and Cooper Union Undergraduate Teaching Assistants
This Four Week Online Program class is open to 10th and 11th graders with the prerequisite.
Prerequisite: Precalculus or calculus with a grade of B or higher
Teaching method: Online, Class starts July 11 and ends August 4. Synchronous Zoom meetings will occur 1-4 PM EST. The instructor and teaching assistants will lead students through daily scheduled lectures, discussions and practice. Additional Office Hours and Study Sessions will be offered at times to be determined.
Materials: A CU@Home kit will be provided to students living in the United States only.
Technology Requirements: Computer with camera and microphone to participate in online video class (Zoom) and use web-based software and file management system (Microsoft Office and Teams). Camera to collect images and video of your project and upload to presentation and portfolio
Cost: $1850
Credits: 0.00
Course Code: STEM22-4