Numerical Optimization and Machine Learning
This course aims at providing students with relevant modern computational numerical techniques using linear algebra, optimization and machine learning, so the undergraduate will be able to attack data science and machine learning problems in an integrated manner.
Basic knowledge of discrete mathematics, calculus and linear algebra. At least one introductory programming course.
On completion of the course, students will:
2 hours a week with a teaching assistant.
Partial exams in each block (25%), projects in each block (25%), homework assignments (50%).