Data Analytics for Poultry and Swine Industries (Edition for NCSU students) - 2023
Full Program (Levels 1, 2 and 3)
The 5th edition starts on August 21st 2024 / Price: us$ 600
About this course
The swine and poultry industries generate enormous amount of information. This could be used to register historical series or as a data base to generate information to improve the results and plan future developments.
Analytical thinking sets the foundation for proper decision making. This process should consider the identification of the problem, the appropriate data collection, the statistical or analytical analysis, the interpretation and communication of the results, and the proper decision making.
The course uses practical examples from the industry and real data shared by some of the main integrations of the world. Utilizes JMP, R and Tableau software with poultry and swine examples. Opens the opportunity for customized data analytic projects. It is a blended course, with self-paced interactive modules and virtual sessions with NC State professors and experts invited from different companies. After completion and evaluation, the Course offers an Extension Certificate in Data Analytics for Poultry and Swine Industries.
The program includes the following topics divided in 3 levels:
Level 1:
- Overview of analytics and potential benefits
- Statistical thinking and problem solving I
- Identifying potential root causes
- Software for data visualization and analytics
- Data visualization and graphics
- Compiling and Collecting Data
- Exploratory data analysis
- Data preparation for analysis
- Decision making with data
- Hypothesis Testing for Continuous Data
- Sample Size and Power
- Statistical process control and quality control
- Correlation and regression to predict responses
Level 2:
- Design of Experiments
- Designing experiments to test factors
- Screening Experiments
Level 3:
- Introduction of predictive modelling
- Multiple Linear Regression Model
- Response Surface Regression
- Non-Linear Models
- Logistic Regression
- Generalized Regression
- Model Comparison and Selection
- Decision Trees
- Neural Networks & Clustering
- Text Mining
- Introduction to Machine Learning
Using this link, you can access a demo of the module on Statistical Thinking and Problem Solving
Director & Instructor: Dr. Edgar O. Oviedo Rondon.
Collaborators: Maria Camila Alfaro and Gustavo Adolfo Quintana.
Instructional Design: Federico Etcheverry
Structure
32 Modules
Length
1800 mins.
Level
Advanced
Meet the instructors
Methodology
Price
USD600.-