Step 1: Basic Python Skills

install Anaconda
including numpy, scikit-learn, and matplotlib

Step 2: Foundational Machine Learning Skills

Unofficial Andrew Ng course notes
Tom Mitchell Machine Learning Lectures

Step 3: Scientific Python Packages Overview

numpy - mainly useful for its N-dimensional array objects
pandas - Python data analysis library, including structures such as dataframes
matplotlib - 2D plotting library producing publication quality figures
scikit-learn - the machine learning algorithms used for data analysis and data mining tasks

Step 4: Getting Started with Machine Learning in Python

iPython Notebook Overview
An Introduction to scikit-learn
Example Machine Learning Notebook
Model Evaluation

Step 5: Machine Learning Topics with Python

k-means Clustering
Decision Trees
Linear Regression
Logistic Regression

Step 6: Advanced Machine Learning Topics with Python

Support Vector Machines
Kaggle Titanic Competition (with Random Forests)
Dimensionality Reduction

Step 7: Deep Learning in Python

Neural Networks and Deep Learning
Theano
Caffe