Data Science Project (390-0-20)

Instructors

Arvind Krishna

Meeting Info

Parkes Hall 212: Tues, Thurs 12:30PM - 1:50PM

Overview of class

In this course, students will work collaboratively on a real-world data science project presented by an actual stakeholder. Meetings with stakeholders will be scheduled based on their availability and the needs of the project. Students will work in teams, with each team focusing on different aspects of the project. Proficiency in tools such as Git and GitHub is expected, along with the ability to collaborate effectively within teams and, when necessary, across teams. The course emphasizes the development of practical skills and offers hands-on experience with modern data science tools and collaborative workflows.

Registration Requirements

STAT 301-3 or STAT 303-3 or consent of instructor. Will be good to have STAT362 completed as well.

Learning Objectives

1. Experience the challenges and the open-ended nature of a real-data science project
2. Experience the opportunity to talk to the stakeholders of a real-data science project (subject to the availability of the stakeholder)
3. Convert the problem between its domain-specific language and data science terminology
4. Learn the commonly used tools and techniques useful in a data science project
5. Perform exploratory data analysis (EDA) and apply modern machine learning methods
6. Learn new data analytics theory, methods, tools, and techniques, if applicable in the project
7. Develop proficiency in collaborative teamwork using version control systems like Git and GitHub
8. Demonstrate the ability to effectively document and present analysis results in a clear and organized manner.

Teaching Method

The students will assigned to teams based on their skills and preferences. Teams will present their progress on the weekly objectives once every week, receive feedback from the instructor, and objectives for next week. The weekly objectives will be decided by the instructor, but will be intended to achieve the stakeholders' goals.

Evaluation Method

A student in this class will be evaluated based on their contribution in achieving the weekly objectives of their team.

Class Materials (Required)

No required textbook.

Class Materials (Suggested)

In-class lecture notes will be provided

Enrollment Requirements

Enrollment Requirements: Registration in this course is reserved for Data Science Majors only Prerequisites: STAT 301-3 or STAT 303-3