Course outline

1. Introduction

2. Type system

• user: tool for abstraction

• compiler: tool for memory layout

3. Design patterns (mental setup)

• Julia is a type-based language

• multiple-dispatch generalizes OOP and FP

4. Packages

• way how to organize code

• code reuse (alternative to libraries)

• experiment reproducibility

5. Benchmarking

• how to measure code efficiency

6. Introspection

• understand how the compiler process the data

7. Macros

• automate writing of boring the boilerplate code

• good macro create cleaner code

8. Automatic Differentiation

• Theory: difference between the forward and backward mode

• Implementation techniques

9. Intermediate representation

• how to use internal the representation of the code

• example in automatic differentiation

10. Parallel computing

• threads, processes

11. Graphics card coding

• types for GPU

• specifics of architectures

12. Ordinary Differential Equations

• simple solvers

• error propagation

13. Data driven ODE

• combine ODE with optimization

• automatic differentiation (adjoints)