Spring 2027

Tools for Data Analysis

Tools for Data Analysis uses bioinformatics tools and computational methods for hands-on analysis of large datasets like genomic and proteomic data to solve biotechnology problems.

offering recorded3 credits
Recorded instructors · Spring 2027 Natalie Betz

Summary

1 / 3

Recent recorded grades — Spring 2024: 3.89 GPA, 100.0% A/AB (n=9 letter grades); Spring 2025: 3.90 GPA, 100.0% A/AB (n=21 letter grades); Spring 2026: 3.90 GPA, 100.0% A/AB (n=15 letter grades).

What you’ll be able to do

  • Describe the revolution in big data related to advances in science and the bottlenecks the corresponding data analytics

  • Explain how several disciplines and specialties within biotechnology analyze and interpret various datasets to address a biological question

  • Develop practical bioinformatics skills applicable to various data types and biological studies

  • Utilize and discriminate between various bioinformatics and data visualization tools to answer research question

  • Construct and deliver effective professional written and oral presentations incorporating scientifically relevant outcomes from various data analytics

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

ABT 700 and 715

ABT 775

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

Recent recorded grades — Spring 2024: 3.89 GPA, 100.0% A/AB (n=9 letter grades); Spring 2025: 3.90 GPA, 100.0% A/AB (n=21 letter grades); Spring 2026: 3.90 GPA, 100.0% A/AB (n=15 letter grades).

Historical instructors & teaching patterns

NATALIE BETZ is recorded teaching in Fall 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025, Spring 2026. 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

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Online Only0 / 1000

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

No records available.

Student experience

the class

Recent recorded grades — Spring 2024: 3.89 GPA, 100.0% A/AB (n=9 letter grades); Spring 2025: 3.90 GPA, 100.0% A/AB (n=21 letter grades); Spring 2026: 3.90 GPA, 100.0% A/AB (n=15 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Bioinformatics tools and computational methods
  • Analysis of large datasets including genomic, proteomic, microbiomics, interactome, and target discovery data
  • Big data revolution in science and data analytics bottlenecks
  • Interdisciplinary dataset analysis in biotechnology to address biological questions

Skills

  • Analyze and interpret large data sets including genomic, proteomic, microbiomics, interactome, and target discovery data
  • Evaluate and adapt existing computational approaches to solve problems in biotechnology
  • Utilize and discriminate between various bioinformatics and data visualization tools to answer research questions
  • Construct and deliver effective professional written and oral presentations incorporating scientifically relevant outcomes from data analytics

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records
ABT 775 · Spring 2027

Tools for Data Analysis

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:160:025301",
    "course_id": "ABT 775",
    "course_uid": "course_6cf7b80b4ca991318368f54d",
    "term_id": "1274",
    "source_course_id": "025301",
    "source_subject_id": "160",
    "title": "Tools for Data Analysis",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
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Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "867e9a93aab15a5dc226926f3a286cbcaeb5d57476f550cf4dbb5b0d732182e5",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}