## ML in R- Course Requirements

This course is designed keeping in mind an absolute fresher out of college. It does not assume that you have a deep knowledge of either R or Statistics or Machine Learning.

However, here is how I would approach the course if you are already familiar with some or all of the topics above.

### If you just know basic R

skip to Day 3 – Numpy and continue from there. Some of the learners of this course have a basic Python background ( either they have worked in Python for Web development or have DevOps background) . In cases like this, days 1 and 2 cover Just enough Python for Machine Learning. Starting from Day 3, we discover Machine Learning and Data Science specific data structures and plotting libraries.

### If you know numpy, pandas and matplotlib

skip to Week 2 where we talk about linear algebra, probability & statistics, and basics of regression and classification in Machine Learning. Once we cover the fundamentals, Week 3 would be really where the grind starts – when we start exploring all the machine learning algorithms in detail.