A Tour of Data Science

Assumptions about the reader's background
Book overview

Introduction to R/Python Programming
Calculator

Variable and Type
Functions
Control flows
Some built-in data structures
Revisit of variables
Object-oriented programming (OOP) in R/Python
Miscellaneous

More on R/Python Programming
Work with R/Python scripts
Debugging in R/Python
Benchmarking
Vectorization
Embarrassingly parallelism in R/Python
Evaluation strategy
Speed up with C/C++ in R/Python
A first impression of functional programming Miscellaneous

data.table and pandas
SQL
Get started with data.table and pandas
Indexing & selecting data
Add/Remove/Update
Group by
Join

Random Variables, Distributions & Linear Regression
A refresher on distributions
Inversion sampling & rejection sampling
Joint distribution & copula
Fit a distribution
Confidence interval
Hypothesis testing
Basics of linear regression
Ridge regression

Optimization in Practice
Convexity
Gradient descent
Root-finding
General purpose minimization tools in R/Python
Linear programming
Miscellaneous

Machine Learning - A gentle introduction
Supervised learning
Gradient boosting machine
Unsupervised learning
Reinforcement learning
Deep Q-Networks
Computational differentiation
Miscellaneous