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.