Part 1: Programming in Python
About Python
Setting up Your Python Environment
An Introductory Example
Python Essentials
Object Oriented Programming
How it Works: Data, Variables and Names
More Language Features
NumPy
SciPy
Matplotlib
Pandas
IPython Shell and Notebook
The Need for Speed
Part 2: Introductory Applications
Linear Algebra
Finite Markov Chains
Shortest Paths
Schelling’s Segregation Model
LLN and CLT
Linear State Space Models
A First Look at the Kalman Filter
Infinite Horizon Dynamic Programming
LQ Dynamic Programming Problems
Rational Expectations Equilibrium
Markov Perfect Equilibrium
Markov Asset Pricing
The Permanent Income Model
Part 3: Advanced Applications
Continuous State Markov Chains
The Lucas Asset Pricing Model
Modeling Career Choice
On-the-Job Search
Search with Offer Distribution Unknown
Optimal Savings
Robustness
Dynamic Stackelberg Problems
Covariance Stationary Processes
Estimation of Spectra
Optimal Taxation
History Dependent Public Policies
Solutions
FAQs / Useful Resources
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