Dr. Michael Chen
Professor of Statistics
Instructor for DATA 301, Fall 2026
- Office
- Ashby Hall 124
- mchen
@university.alkimi.ai
DATA 301 · Data Science
Data Mining and Predictive Modeling
Supervised learning models, classification and regression trees, random forests, support vector machines, clustering algorithms, and model validation techniques.
Catalog overview
Course Essentials
- Credits
- 3
- semester credit hours
- Level
- 300
- Upper division
- Typically offered
- Fall
- Fall semester only
Prerequisites
300-level courses: advanced, upper-division courses requiring prior foundational preparation. This course counts toward the 36 upper-division credits every bachelor's degree requires (Undergraduate Catalog §2.3). Details: Undergraduate Catalog §9.5.
Generative AI in this course
Every syllabus must state one of three levels: Level 1 (AI not permitted for graded work), Level 2 (AI permitted with disclosure for specified tasks), Level 3 (AI permitted broadly with disclosure). Check your section's syllabus in Canvas. Unless it says otherwise, the university default applies: generative AI tools may be used for brainstorming, studying, and feedback on your own drafts, but not to produce work you submit for a grade.
Details: Student Handbook §5.7 and Student Handbook §5.8. See what each AI level allows.
Offered by
Data Science Program
Questions: Academic Advising Center
- Office
- Lovell Hall 101
- Phone
- (555) 555-0158
- advising@university.alkimi.ai
Degree planning
Where DATA 301 fits
What to take first, what this course opens up, and the requirements it can satisfy, from the Undergraduate Catalog.
Take first
This course
DATA 301
Data Mining and Predictive Modeling
3 credits · 300-level · Fall
Counts toward
- Required Data Science (BS) Required course (Major Requirements & Supporting Disciplines). Undergraduate Catalog §6.3
Every course also counts toward the 120 credits needed for a bachelor's degree. Confirm your plan with your advisor or the Academic Advising Center.
AP credit
No AP exam awards credit for DATA 301. See the full AP equivalency table (Undergraduate Catalog §3.11).
2026–27 Instructors
Who teaches DATA 301
Meeting times and rooms for each term are listed in AlkimiHub when registration opens.
Department chairs make teaching assignments each year (Faculty Handbook §5.1), and every instructor posts the syllabus in Canvas by the first day of classes (Faculty Handbook §5.2).
Registration
How to enroll in DATA 301
-
Add it in AlkimiHub
DATA 301 is typically offered in the fall semester. Register through AlkimiHub self-service registration, which opens by credit standing. Until the add deadline, you don't need instructor permission as long as seats remain and you've met the prerequisites. Details: Student Handbook §3.3.
-
If the section is full, join the waitlist
When a seat opens, AlkimiHub offers it to the first student on the waitlist and emails you. You have 24 hours to claim it before it goes to the next student. Details: Student Handbook §3.10.
Fall 2026 add deadline
Last day to add a course or change sections (11:59 p.m.).
Fall 2027 registration opens
By credit standing, in AlkimiHub.
All dates: academic calendar. Registration help: Office of the Registrar.
DATA courses
More in Data Science
- DATA 201 Introduction to Data Science & Analytics
- DATA 301 Data Mining and Predictive Modeling (this course)
- DATA 350 Big Data Infrastructure & Distributed Computing
- DATA 401 Machine Learning and Neural Networks
- DATA 490 Senior Data Science Capstone Project