There are many programming languages, and a few of them are prominently used in Scientific Computing. This lesson offers a brief review of a few of the most currently used open programming languages in science. The lesson focuses on the strengths of each individual language and how to mix them to get the most out of them.
Prerequisites
This tutorial requires familiarity with command line interface. The lessons do not assume previous knowledge of these programming languages, but at least the knowledge of one can help you understand the differences in syntax between them.
| Setup | Download files required for the lesson | |
| 09:00 | 1. The Sieve of Eratosthenes | How one algorithm looks in 7 different languages? |
| 10:00 | 2. Interpreted Languages (Python and R): A comparative review | If I know one language, how I can do a similar thing on the other? |
| 11:00 | 3. C/C++: Traditional Computing | Why most C is the most influential language in computing? |
| 11:30 | 4. Fortran: Intensive Numerics | Why to use Fortran if it is so old? |
| 12:00 | 5. Lunch Break | Break |
| 13:00 | 6. Julia: The best of two worlds | What is Julia, and why should I learn another language? |
| 14:00 | 7. Cython: Accelerate Python Execution | What is Cython and its relation with Python? |
| 15:00 | 8. Fortran inside R | How to accelerate numerical intensive operations in R |
| 16:00 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.