International course on Big Data and digital tools applied to livestock production
*COURSE IS FULL*
VENUE: Institut Pasteur - Mataojo 2020, Montevideo, Uruguay.
LANGUAGE OF INSTRUCTION:English
APPLICATIONS NO LONGER ACCEPTED.
*Participants must bring their own laptop.
ACCOMMODATION:Participants must arrange their own travel and accommodation.
TOPICS:
- Big Data and Data Science in Livestock
- Planning Research Studies in Animal Sciences
- Database Management
- Multidimensional Regression and Classification
- Machine Learning Techniques
- Image Processing and Analysis
- Infrared Spectroscopy and Hyperspectral Imaging
- Wearable Sensing Technology
- Deep Learning
- Genomics Data
- Mining Operational Farm data
- Cloud Computing
DESCRIPTION: Graduate level course (PhD and advanced MS) for researchers working in all areas of animal sciences, such as nutrition and physiology, management, genetics and reproduction, in industry or academia, especially those interested in data analytics and precision management of livestock. Statisticians, computer scientists, and data scientists interested in learning about potential applications in animal science can also benefit from the course. The course will cover key concepts and techniques related to statistics and machine learning applied to high-dimensional data in livestock, including data from sensors, imaging, genomics, farm-recorded data from management software, and publicly available datasets. The course includes expository lectures and demonstrations with real data and useful software and algorithms shared with the participants.
INSTRUCTORS:
Dr. Guilherme Rosa (https://www.gjmrosa.org/): Professor at the Department of Animal & Dairy Sciences and Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison.
Dr. Joao Dorea (https://andysci.wisc.edu/directory/joao-ricardo-reboucas-dorea/): Assistant Professor at the Department of Animal & Dairy Sciences and Department of Biological Systems Engineering, University of Wisconsin-Madison.
CONTACT:
Dr. Daniel Gianola (dgianola@inia.org.uy)
Dr. Olga Ravagnolo (oravagnolo@inia.org.uy)
TENTATIVE SCHEDULE:
09:00 - 10:30 Class: Dighiero Conference Room
10:30 - 10:50 Coffee break
10:50 - 12:15 Class:Dighiero Conference Room
12:15 - 13:30 Lunch
13:30 - 15:00 Lab Group 1 (50 % of participants):Computing Laboratory
15:00 - 15:30 Coffee break
15:30 - 17:00 Lab Group 2 (remaining 50 %):Computing Laboratory
