I'd recommend you to start with data visualization, intute how mean, median, variation don't capture the data, then move onto normal distribution approximation

I'd recommend you to start with data visualization, intute how mean, median, variation don't capture the data, then move onto normal distribution approximation of dataset, then linear regression and finally bayesian classification/probability models. Only after you get a good grasp on basics should you move to advanced topics such as neural networks, SVMs, etc.