Table of Contents (Graduate course)¶

• All
• Undergraduate course
• Graduate course

• About these Lectures
• Getting Started with Julia
  • Setting up Your Julia Environment
  • Interacting with Julia
  • Introductory Examples
  • Julia Essentials
  • Arrays, Tuples, Ranges, and Other Fundamental Types
  • Introduction to Types and Generic Programming
• Packages and Software Engineering in Julia
  • Generic Programming
  • General Purpose Packages
  • Data and Statistics Packages
  • Solvers, Optimizers, and Automatic Differentiation
  • Julia Tools and Editors
  • Git, GitHub, and Version Control
  • Packages, Testing, and Continuous Integration
  • The Need for Speed
• Tools and Techniques
  • Linear Algebra
  • Orthogonal Projections and Their Applications
  • LLN and CLT
  • Linear State Space Models
  • Finite Markov Chains
  • Continuous State Markov Chains
  • A First Look at the Kalman Filter
• Dynamic Programming
  • Job Search I: The McCall Search Model
  • Job Search II: Search and Separation
  • A Problem that Stumped Milton Friedman
  • Job Search III: Search with Learning
  • Job Search IV: Modeling Career Choice
  • Job Search V: On-the-Job Search
  • Optimal Growth I: The Stochastic Optimal Growth Model
  • Optimal Growth II: Time Iteration
  • Optimal Growth III: The Endogenous Grid Method
  • LQ Dynamic Programming Problems
  • Optimal Savings III: Occasionally Binding Constraints
  • Robustness
  • Discrete State Dynamic Programming
• Multiple Agent Models
  • Asset Pricing II: The Lucas Asset Pricing Model
  • Uncertainty Traps
  • The Aiyagari Model
  • Default Risk and Income Fluctuations
  • Globalization and Cycles
• Time Series Models
  • Covariance Stationary Processes
  • Estimation of Spectra
  • Additive Functionals
  • Multiplicative Functionals
  • Classical Control with Linear Algebra
  • Classical Filtering With Linear Algebra
• References