There are eight microcredentials within the Precision Farming series and they can be taken in any order or on their own.
Venturing into data analysis can be daunting. However, much of the analysis required for agriculture operations may be less complex. For example, regression analysis can provide insight into production levels based on single focus items such as rainfall for the year. However, to analyze combinations of factors such as rainfall, soil condition, hours of sunlight, seed density and fertilizer application rates, requires machine learning (ML)/AI to provide a more in-depth picture of what is happening. This microcredential introduces participants to analyzing data and format approaches, algorithms for decision-making, and interpreting the results of compiled data.
Microcredentials in this series:
Upon completion of this microcredential, learners will be able to:
Precision farming practices using the latest techniques and technologies address various aspects of carbon footprint and clean technologies. For example, using data of field conditions and states of weed growth, the latest sprayer technology can target spray weeds without carpet-spraying the entire field.