Lecture
Practical Machine Learning
Course and term details
- Sequence
- 01
- Part of term
- 1
- Term
- Fall 2026
- Linked section
- No
- Open section
- Yes
Fall 2026
COSC4557 CRN 14845Practical Machine Learning
LectureMainShukla, DikshaTue Thu 9:35 a.m. – 10:50 a.m.
Section data from the UW course catalog via uwyoschedule. Confirm seats and meeting times in WyoWeb before you register.
Schedule
Tue, Thu
9:35 a.m. – 10:50 a.m.
Engineering Building 1055
08/31/2026 – 12/11/2026
Meeting type
Class · LEC
Faculty
Shukla, DikshaPrimary
dshukla@uwyo.edu
Seats
20
open of 20 seats
Enrollment and waitlist
- Enrollment
- 0
- Maximum enrollment
- 20
- Seats available
- 20
- Wait capacity
- 5
- Wait count
- 0
- Wait seats available
- 5
Credits
3
3
All credit fields
- Credit range
- 3
Course description
The class addresses the challenge of designing well-performing Machine Learning (ML) pipelines, including their hyperparameters, architectures of deep Neural Networks, and pre-processing. Future ML developers will learn how to use and design automated approaches for determining such ML pipelines efficiently.
Attributes
1
TPN1 · Program Fees - Engineering
Full attribute list
- TPN1
Program Fees - Engineering
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