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Courses may be offered in one of the following modalities:

  • Traditional in-person courses (0–29 percent of coursework is delivered online, the majority being offered in person.)
  • Hybrid/blended courses (30–79 percent of coursework is delivered online.)
  • Online courses (100 percent of coursework is delivered online, either synchronously on a designated day and time or asynchronously as a deadline-driven course.)
  • Hyflex (Students will be assigned to attend in-person or live streamed sessions as a reduced-size cohort on a rotating basis; live sessions are also recorded, offering students the option to participate synchronously or view asynchronously as needed.)

If you are enrolled in courses delivered in traditional or hybrid modalities, you will be expected to attend face-to-face instruction as scheduled.


DSC 681: Applied Machine Learning

3 credits

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.

Learning Goals

Upon completing the course, the students will:     1. Describe the scope of Machine Learning and is importance in a Business Environment2. 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 Techniques6. Explain the difference between supervised and unsupervised machine learning7. Illustrate stationary, trend and, seasonal time series patterns and their application in Forecasting

*The learning goals displayed here are those for one section of this course as offered in a recent semester, and are provided for the purpose of information only. The exact learning goals for each course section in a specific semester will be stated on the syllabus distributed at the start of the semester, and may differ in wording and emphasis from those shown here.

Sections Offered: Fall 2024

Applied Machine Learning
0207-681-001 Y. Han Oct 24 - Dec 19 Thu 5:45 pm - 9:45 pm GC - HHE 209 3
0207-681-002 Y. Han Oct 21 - Dec 19 Mon 5:45 pm - 9:45 pm GC - HHE 209 3

Sections Offered: Summer 2024, Summer I

Applied Machine Learning
0207-681-001 TBA May 29 - Jul 3 Mon/Wed 5:00 pm - 8:00 pm Online 3

Sections Offered: Spring 2024

Applied Machine Learning
0207-681-001 J. Mroz Apr 1 - May 16 Mon 5:45 pm - 9:45 pm GC - SWL 114 3
0207-681-002 Y. Han Mar 30 - May 18 Sat 1:00 pm - 4:20 pm GC - HHE 112 3

 
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