Advancing Dairy Management with Artificial Intelligence

Overview

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By completing this course, you will gain a solid understanding of the basics of AI and its role in dairy systems. You will learn to identify key data types used in dairy analytics, such as production, health, and nutrition data. Additionally, you will explore AI applications in various aspects of dairy systems and discuss current AI applications in the dairy industry. This course, led by Dr. Isabella Condotta, offers a unique opportunity to understand how AI can revolutionize dairy data analysis. You will explore AI models for health monitoring, sensor technologies, and predictive models. The course also covers biomarker profiling to assess cow health and nutrition, and a systems approach to nutritional management for optimal production. Join us to gain cutting-edge insights into AI applications in dairy systems and enhance your ability to make data-driven decisions for improved dairy management. This course is part of the College of ACES suite of online programs, including the graduate certificate, "Dairy Nutrition for Udder Success" that can be stacked toward an advanced degree in the College of ACES. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online @ aces.illinois.edu/online.

Syllabus

Orientation & Module 1 | Introduction to Artificial Intelligence in Dairy Farming

In the course orientation, you will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course. Then dive into the second part of this module which introduces key AI technologies and their applications in dairy farming. You will explore how data analysis and IoT are transforming dairy practices, along with the advantages and challenges of AI implementation.

Module 2 | Data Collection and Management in Dairy Farming

This module focuses on the types of data collected in dairy farming and their significance. You will learn about traditional and modern methods of data collection, best practices for effective data management, and various tools and software used for managing dairy data. The importance of maintaining high-quality data in dairy farming will also be highlighted.

Module 3 | Artificial Intelligence Techniques for Dairy Data Analysis

This module delves into the fundamentals of machine learning, including supervised and unsupervised learning techniques, and their relevance to dairy data. You will learn the steps to apply machine learning algorithms in dairy farming, with practical examples and real-world applications of AI in this field.

Module 4 | Predictive Analytics and Decision Support Systems & Conclusion

This module explores predictive analytics and its importance in dairy farming. You will learn about building predictive models, decision support systems, and emerging AI trends in the field. At the conclusion of this module, you will be ready to complete the final assessment for the course and earn your Coursera certificate!