Faculty of Natural Sciences The National University of Salta (UNSa) confirmed that “Postgraduate Diploma in Data Science Applied to Natural Systems.”
The educational proposal will be coordinated by the Doctor of Geological Sciences, Juan Gonzalo Visaga SaavedraThey are also responsible for preparing the diploma Gustavo Landfried and coach Ariel Ramos.
Dean of Natural Sciences Julio Nacer with Dr. Juan Visaga, Diploma Coordinator.
The Diploma in Data Science offers comprehensive training through five carefully designed modules to address the different aspects and applications of this discipline.
the first unit“Programming Basics” Students are immersed in the basic concepts of programming and their importance in the context of data science. From acquiring skills in different programming languages to data visualization, this unit lays the foundation needed to understand and apply the basic principles of data science.
In the second module, “Methods and Techniques in Data Science,” participants delve into advanced techniques such as machine learning, data mining, and applied statistics. This module provides a deeper understanding of how to apply these tools to analyze complex data sets and extract meaningful insights. With a solid foundation in the first two modules, the next three modules focus on practical applications in various fields:
1. Applications in Earth Sciences: It focuses on forecasting exploration and production models, analyzing large geological and geophysical data sets in order to identify patterns and trends that can aid in the exploration and extraction of natural resources, such as minerals, oil and gas. This involves using predictive analysis techniques to estimate the location and viability of natural resource deposits.
2. Applications in agricultural engineering: This unit focuses on the application of data science in the field of agricultural engineering, with an emphasis on agricultural data analysis (agricultural analytics). Students will learn how to use data science techniques to improve agricultural production, improve crop and soil management, and optimize the use of resources such as water and fertilizer. Additionally, it will explore how agricultural data can be used to predict productivity, detect plant diseases and make informed decisions to increase productivity and sustainability in agriculture.
3. Applications in natural resources and the environment: This unit focuses on the application of data science to the management and conservation of natural resources and the environment. Data analysis tools and techniques are used to address challenges such as biodiversity, environmental monitoring and sustainable management of natural resources. From species identification to environmental impact assessment of development projects, these applications provide innovative and sustainable solutions.
4. Applications in biology: In this field, data science is used to address a variety of fields, including genomics, ecology, and evolutionary biology. For example, in genomics, data science techniques are used to analyze large genetic data sets to better understand the structure and function of the genome. In ecology, scientists use data science to study species distribution patterns, the effects of climate change on ecosystems, and population dynamics. Additionally, in evolutionary biology, data science helps understand how species evolve and adapt to their environment by analyzing genetic and phenotypic data.
5. Applications in education: Data science and artificial intelligence are revolutionizing education by providing powerful tools to personalize teaching, improve learning, and improve educational processes. Data science is used to analyze student performance, identify learning patterns, and evaluate the effectiveness of different pedagogical approaches. On the other hand, AI can recommend specific educational resources based on each student's interests, skill level, and learning style. As for automated grading systems, they can evaluate student work quickly and objectively, freeing up time for teachers to focus on more interactive, high-value activities.
The diploma consists of five courses that will be taught online. Workload: 210 hours.
