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.
Common requirements for the semester and some knowledge of discrete mathematics.
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%).