# Courses

## Discrete Optimization Reading Club

Platform: YouTube

Link: https://youtube.com/playlist?list=PLM6kVvFMcINMZpblkY0l2-p0wgIqf79oW

I read papers about MIP, CP, and SAT solver development and summarize the main ideas in simple language. I am developing this as a personal library of discrete optimization solver advancements. This can be useful to students starting their journey in operations research.

## Linear Programming Basics

Platform: Udemy

Link: https://www.udemy.com/course/linear-programming-basics/?referralCode=6AC1EEE79F44361FD025

Coupon code: -

Linear programming is a widely used optimization tool in various application (data science, engineering, transportation, supply chain, etc.). Linear programming also makes the basic foundation behind complex optimization tools like Mixed Integer Liner Programming (MILP) and Column generation. In this course, we will study the basic theoretical concepts related to linear programming.

## Introduction to scikit-learn

Platform: Codedamn

Link: https://codedamn.com/learn/scikit-learn

Coupon code: -

Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. Scikit-Learn is characterized by a clean, uniform, and streamlined API. It also provides various tools for model fitting, data preprocessing, model selection and evaluation, and many other built-in machine learning algorithms and models. In this course, I provide a basic introduction to scikit learn and machine learning.

## Probability for Machine Learning

Platform: Udemy

Link: https://www.udemy.com/course/probability-for-machine-learning/?referralCode=D5D01EE11F93740E6C74

Coupon code: -

Probability is usually a prerequisite of machine learning. However, one doesn't need to know all the concepts in probability. In this course, I have compiled together all the important probability concepts that are most frequently used in machine learning. This is the content I taught at Polytechnique Montreal as a refresher on probability for machine learning. Understanding these concepts will help you navigate through an introductory course in machine learning.

## Linear algebra for Machine Learning (basics + python implementations)

Platform: Udemy

Link: https://www.udemy.com/course/linear-algebra-basics-for-machine-learning/?referralCode=C312EEE016563B47CE2A

Coupon code: -

Linear Algebra is typically a prerequisite of machine learning. However, one doesn't need to know all the concepts in linear algebra. In this course, I have compiled together all the essential linear algebra concepts that are most frequently used in machine learning. This is the content I taught at Polytechnique Montreal as a refresher on linear algebra for machine learning. Understanding these concepts will help you navigate through an introductory course in machine learning.