Becoming a data scientist is intrinsically linked to being upto date on statistics and the underlying math along with other practical skills. But how much math do you need? And how do you actually pick up the math? Here is a brief video on learning the math for ML.

##### What Math is required for ML

The three basic math topics required to get a deeper understanding of Machine Learining are

- Linear Algebra
- Probability and Statistics
- Calculus and Optimization

##### Resources and Online Courses for learning Math for Machine Learning

Khan academy has a great course on probability and statistics. Very elaborate and intuitive explanation of concepts.

https://www.khanacademy.org/math/statistics-probability

Here is a coursera specialization that covers all of Linear Algebra, probability & statistics and optimization.

https://www.coursera.org/specializations/mathematics-for-data-science

Another coursera specialization that covers linear algebra mostly and a bit of optimization.

https://www.coursera.org/specializations/mathematics-machine-learning