DSC (0207) 681 - Applied Machine Learning

Credits: 3.00

Students will acquire key concepts in applied machine learning and will use software packages and applications that are relevant today such as R and Python. The course applies principles of machine learning to business problems. Topics include linear regression models, classification methods and times series forecasting.

Prerequisite 1: CSC 602 DSC 575 DSC 670
Repeatable: No Grade Type: Regular
Course Learning Goals: Upon completing the course, the students will:

1. Describe the scope of Machine Learning and is importance in a Business Environment

2. Analyze real world scenarios and select the appropriate Machine Learning techniques to utilize.

3. Develop Machine Learning models that can support an Organizations decision process

4. Generate solutions using R and/or Python popular packages

5. Examine the results obtained using different Machine Learning Techniques

6. Explain the difference between supervised and unsupervised machine learning

7. Illustrate stationary, trend and, seasonal time series patterns and their application in Forecasting