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Clinical Microbiology: Phenotypic Identification of Common Organisms
Clinical microbiology lab practice focusing on phenotypic identification of common bacteria, fungi, and parasites through specimen handling and culture techniques.
Summary
Lectures are mid-sized, with a median of 46 enrolled students in the recorded sections.
Grade history
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Prerequisites
Course mapMED SC-M 810, 811, 812, and 813
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
Professors
Fall 2026Historical instructors & teaching patterns
DERRICK CHEN is recorded teaching in Spring 2024, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 020 | Online Only | 46 / 0 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Meeting source records
Student experience
the class
Clinical microbiology lab practice, with a focus on identification of bacteria, fungi, and parasites. Learn techniques in specimen collection, staining, and plating. Gain an understanding of culture media, incubation, isolation, and microscopic and colony characteristics.
difficulty & workload
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Catalog & offerings
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Catalog observation history
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Selected offering source records
Clinical Microbiology: Phenotypic Identification of Common Organisms
Recorded 2026-09-07Raw records
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"semester": "1272",
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"offering_id": "1272:704:026574",
"course_id": "PATH 914",
"course_uid": "course_cebd2c6628d27f0eaea7dca3",
"term_id": "1272",
"source_course_id": "026574",
"source_subject_id": "704",
"title": "Clinical Microbiology: Phenotypic Identification of Common Organisms",
"credits_min": 2,
"credits_max": 2,
"typically_offered": "Not Applicable"
}
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Grade history
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Explore recorded gradesModel outputs & technical records
LLM outputs across runs
Full model traces
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Model & dataset provenance
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