This is a guide that I created to self-teach data science and machine learning. There are tons of resources online, but I feel a consolidated and complete guide will help me learn better. I will use Jupyter Notebooks to run code in Python and R. Here is the curriculum, which will be updated as material gets added:

• Python 3
  • Data Types and Structures
  • Logic and Loops
  • Methods, Objects, and Classes
  • Advanced Python
• R for Data Science
• Statistics (Calculus-based)
  • Descriptive Statistics
  • Set Theory
  • Probability
  • Discrete Probability Distributions
  • Continuous Distributions
  • Joint Probability Distributions
  • Point Estimation
  • Confidence Intervals
• Numpy
• Pandas
  • Data Frames
  • Data Manipulation
  • Pivot Tables
• Matplotlib
• Data Analysis Techniques
  • Regression
  • K-Means Clustering
• Scikit Learn
• Tensorflow

More to come...