My first contact with programming languages started as an undergraduate student, I had the opportunity to work on a Forecast model to predict hail fall over Cuba using an Artificial Neural Network. The model trained was a two-densely connected layers Multilayer Perceptron which used three meteorological predictors in the input layer. It achieved an 87% accuracy during inference. I got familiarized with Matlab, WEKA and Python.
After graduating, I joined the Cuban Meteorological Institute (Insmet) where I started my career as Scientific Researcher. I had the opportunity of learning Django Django to automate HYSPLIT dispersion and trajectory daily runs fed by the outputs of the regional forecast model MM5V3.
The experience I gained during this period was invaluable, as it helped me understand the software development lifecycle from a user perspective and to improve my problem-solving skills.