STAT 654 - Introduction to Applied Deep Learning

Units: 2
Introduction to neural networks and deep neural networks, training a prediction model, avoiding over-fitting, tuning. Prediction and classification problems. Using R packages or Python to connect to h20, tensorflow, keras. Report Writing.

Prerequisites: STAT 632.
Co-requisites:

Possible Instructional Methods: On-ground, or Hybrid or Online-Asynchronous.
Grading: ABC/NC grading only.
Course Typically Offered: Spring ONLY

Student Learning Outcomes - Upon successful completion of this course students will be able to:

Demonstrate knowledge of neural networks.
Use deep learning models for prediction and classification.
Effectively communicate results from the use of statistical packages in a discipline-appropriate manner.