BSC 6895C: AI in Agriculture and Life Sciences
- Credits: 3
- Prerequisites: microbiology
- When Offered: Fall
- Syllabus: BSC 6895C: AI in Agriculture and Life Sciences
Description
Artificial intelligence (AI) is used to solve problems in research and industry. This course provides students with an understanding of AI systems and how they can be applied to answer challenging questions in life sciences. Through online study materials and hands-on exercises, students will obtain the skills and knowledge they need to use AI to solve real-world life sciences problems.
Course Goals
By the end of this course, students will be able to:
- Implement multi-neuron layers and multi-layer networks to build general nonlinear neural networks in TensorFlow.
- Diagnose model overfitting in TensorFlow using validation data, and implement and evaluate standard methods to mitigate overfitting in TensorFlow.
- Use Google Colaboratory (Google Colab) and Jupyter Notebooks to build and train neural networks.
- Apply correct vocabulary to characterize neural networks, modern AI, and the history of AI development.
- Identify important applications of phenotype prediction in agricultural and life sciences.
- Define overfitting and use AI vocabulary to describe how overfitting is evaluated in practice.
At a Glance
| Tuition | $535*/credit |
| Format | 100% Online |
| Credits | 30 Credit Hours |
| Application Deadlines | |
| Spring 2027 | November 15 |
| Summer 2027 | April 1 |
| No Application Fee | |