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| Semester: | Summer 2024 |
| Number: | 0207-783-001 |
| Instructor: | Michael Odonnell |
| Days: | Tuesday Thursday 5:00 pm - 8:00 pm |
| Note: | Hybrid Online/In-Person Class |
| Location: | Garden City - Hagedorn Hall of Enterprise 113 |
| Credits: | 3 |
| Course Meets: | May 29 - July 3 |
| Course Materials: | View Text Books |
| Related Syllabi: |
Michael Odonnell for
Spring 2024* |
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*Attention Students: Please note that the syllabi available for your view on these pages are for example only. The instructors and requirements for each course are subject to change each semester. If you enroll in a particular course, your instructor and course outline may differ from what is presented here. |
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| Description: |
Students will learn the structure and steps used in the development of a business data analytics solution. Advanced analytical techniques will be included such as support vector machines and neural networks. Students will use state of the art Python and R packages such a Pytorch, Keras, and Tensor Flow. |
| Learning Goals: |
Upon completing the course, students will: 1. Explain the process of a successful Machine Learning project2. Illustrate the use of Machine Learning in a business environment3. Synthetize the principles of neural network models and its similarity with the brain4. Formulate models that solve classification problems 5. Solve classification problems using state of the art software applications6. Evaluate solutions obtained by different classification techniques7. Compare software applications and packages used to solve classification *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. |
| Prerequisites: |
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