Steve Bennoun is an Active Learning Lecturer in the Department of Mathematics. Dr. Bennoun completed his undergraduate degree at the École Polytechnique Fédérale de Lausanne in Switzerland and his PhD at the University of British Columbia in Canada. His research is focused on algebra and category theory and he has presented his work at several national and international conferences. Dr. Bennoun has also published articles in journals such as the Journal of Algebra. At Cornell, Dr. Bennoun’s research is focused on how to enhance student learning in mathematics courses by introducing active learning methods, a topic about which he is writing a book.
This Machine Learning certificate program requires you to think and solve problems in multiple dimensions. In this course, you will learn to solve linear algebra problems in three or more dimensions and perform computations with matrices.You will perform computations that focus on solving problems in high dimension; that is, multiple dimensions. This course will provide you with the theory and activities to solidify the linear algebra foundation needed to be successful in your Machine Learning courses.
This optional self-paced course supports the required linear algebra in the Machine Learning certificate. If you are already comfortable with the computations from the pretest, we recommend that you take the final assessment to confirm your readiness.
- Test whether n dimensional vectors are orthogonal
- Define n dimensional planes in space
- Compute the distance to a plane in high dimension
- Perform basic computations with matrices
How It Works
Who Should Enroll
- Data analysts
- Data scientists
- Software engineers