|
|
|
|
Recent News:
|
Guest lecture on April 12, 2021 by Prof. Anjana Susarla .
Lally wellness day on April 15, 2021 -- no class.
|
|
Course Description:
|
The widespread proliferation of IT-influenced economic activity leaves behind a rich trail of micro-level data, enabling organizations to use analytics and experimentation in both strategy and operations. This course provides a hands-on introduction to the concepts, methods and processes for machine learning from data, the foundation of artificial intelligence. We will learn how to manipulate data and apply machine learning models to business contexts.
Towards this goal, students will:
- Demonstrate an understanding of analytics-based problem solving and analytics thinking in the context of machine learning models, deep learning, and big data.
- Be able to extract, match, transform, and clean data from a variety of sources.
- Develop machine learning predictions for business applications.
- Apply ethical frameworks to the creation of models.
- Translate research on state of the art deep learning to business applications.
|
|
Prerequisites:
|
The goal of this course will be to provide the technical foundation to enable students to become data scientists.
It is preferable that students have had background in coding experience in Python but not compulsory.
|
|
Office hours:
|
Location: Webex (Check the syllabus for the url)
|
|
Contact Info:
|
manikl@rpi.edu
|
|
TA:
|
Yuanyuan Liu
Email: liuy55@rpi.edu
Office hours: Friday 11 am -- 1 pm
|
|
Grading:
|
| Final Exam: | 30% |
| Project: | 25% |
| Midterm: | 25% |
| Assignments and quizzes: | 15% |
| Research Translation Exercise (for MGMT 6560 only): | 5% |
Missing an assignment or a test without prior approval from the instructor will result in a grade of zero (0). There will be no opportunities for extra credits or make-up assignments.
|
|
Syllabus:
|
Course syllabus can be downloaded from here.
|
|
Textbooks (not required but prefered):
|
|
|