About

Statistics 654: Introduction to Applied Deep Learning (2 units)

Course Description:

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:

Post-baccalaureate standing.

Possible Instructional Methods:

Entirely On-ground, or Entirely Online, or Hybrid.

Grading:

A-F or CR/NC (student choice).

Student Learning Outcomes

Upon successful completion of this course students will be able to:

  1. Use software to learn from data.
  2. Critically evaluate learning models.
  3. Extract data from large data source to learn from data.
  4. Create reproducible reports.