Artificial Intelligence for Renewable Energies
NEW DATES AND TIMES: TBD
With growing interest from governments, consumers, and industry participants around the world in increasing energy production from renewable energy sources, our challenge is to improve the quality of understanding and knowledge for those interested in green and environmentally friendly energies.
The Artificial Intelligence for Renewable Energies course is designed for participants to acquire the theoretical and practical knowledge to apply concepts of Artificial Intelligence in the field of Renewable Energies such as solar, wind, geothermal, and hydro.
Starting with an introduction to the main concepts of programming in Python, the participant will learn the basic concepts of Machine Learning and Deep Learning algorithms for the analysis of time series related to patterns of consumption of water and energy resources, as well as in the estimation of energy resources associated with solar, wind, and geothermal energy, and the use of satellite images through neural networks for the classification of the earth's surface.
Participants won’t need previous programming experience in Python, and no software is required. We will use Google CoLab platform to program the exercises.
Objectives
- Learn to use the main features of Python 3, as well as the packages selected most important of this language (Numpy / SciPy / Pandas / Matplotlib), through a project in Jupyter Notebook and Google Colab.
- Know and apply the basic concepts of Artificial Intelligence, as well as the main Machine Learning and Deep Learning algorithms, applied to data on water resources and green energy.
- Apply techniques of analysis and visualization of geoscientific data using the libraries from Python.
- Interpret the output obtained by the prediction models.
- Learn to use the main Machine Learning libraries today (Scikit - Learn), and Deep Learning (Keras, TensorFlow and PyTorch).
