This course provides a practical introduction into machine learning (ML). It will give an intuition for ML algorithms, without going deep into mathematical proofs. We will focus on applying ML algorithms for real-life problems. The content of the course is suitable for researchers and data scientists who either have no previous exposure to machine learning, or are aspiring to improve their practical skills in using machine learning to tackle real-world problems. We will implement some of the algorithms to gain a deep understanding and also use the Scikit-learn library, which provides a high- level interface to a large number of machine learning algorithm. Codes are in the Julia language, which is a programming language specially suitable for scientific computing.

## Grading

**Note:**Grading

- Each exercise, as well as the final project, has a certain number of points written next to it. The final grade is the sum of all the points gained. The final project has 30 points.