| 1. List Comprehensions. Before we can start, we have to set ourselves up first: install Julia and a couple of other tools. |
2. Application Areas In this section we will acquaint ourselves with some basic commands, and carry out some simple numerical exercises. |
3. Machine Learning (Part 1). In this section, we will show how Julia is used to carry out simple machine learning tasks |
4. Problem Set 1. To get a grasp of how Julia works, we will start off with some simple mathemathical and statistical exercises. |
| Machine Learning (Part 2). In this section, we will show how Julia is used to carry out some more machine learning tasks |
6. Data Types. In this section, we will look at FOR loops and IF ELSE statements. |
7. Matrices Matrices and Linear Algebra are hugely important in numerical programming. In this secion, we look at the main Julia commands. |
8. Problem Set 2. This second problem set will test your skills on the last three sections. |
| 9. Probability Distributions. How to generate a random numbers with Juila. |
10. Statistics. Statistical Operations with Julia |
11. Writing Functions. How to write your own functins. Conical pendulum. Circular orbits. |
12. Problem Set 3. This second problem set will test your skills on the last three sections. |
| 13. Special Arrays It is always very useful to know these in numerical computing |
14. Array Operations How to transform and reshape arrays. |
15. Using Packages | 16. Problem Set 4. This problem set will test your skills on the last three sections. |