Numerical Optimization and Machine Learning
COURSE DESCRIPTION 
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. Prerequisites Basic knowledge of discrete mathematics, calculus and linear algebra. At least one introductory programming course. 
COURSE GOALS 
On completion of the course, students will:

COURSE CONTENT 
Bibliography
Support Sessions 2 hours a week with a teaching assistant. Grading Partial exams in each block (25%), projects in each block (25%), homework assignments (50%). 