In case you are not familiar with Siraj Raval’s “Learn Machine Learning in 3 Months” curriculum check out this video: http://aitu.be/Siraj3

Week 3 of this curriculum was about probability through the MIT edX Course “Introduction to Probability“. The time recommended to take this course is 18 weeks and completing the course in one week proved very hard, even with videos at 2x speed. The pragmatic solution I chose was to complete the summary videos and focus on specific subjects that are essential for Machine Learning, like Bayesian Inference and Conditional Probability.

Happily, the course of week 4 is more realistic to complete in a week. The edX course “Algorithm Design and Analysis” consists of four units and it is doable to complete a unit a day.

Let’s go!

**Month 1: Math and Algorithms**

Week 1: Linear Algebra

Week 2: Calculus

Week 3: Probability and Statistics

**Week 4: Algorithms**

Next week: Courses by Siraj Raval on Python for Data Science, Machine Learning Models and Tensorflow (Playlist)

For the full curriculum check out Siraj Raval’s Github: https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months