DANL 101
  • Brightspace
  • Materials
    • Lecture Slides
    • Classwork
    • Homework
    • Exams
  • Project
    • Guideline
    • Topics
  • R
    • 101-01
    • 101-02

  • Start Here
    • Home
    • Semester map
    • Syllabus
  • Weekly Roadmap
    • 01 · Analytics workflow
    • 02 · R foundations
    • 03 · Stats with R
    • 04 · Databases + data
    • 05 · Transform data
    • 06 · Join + visualize
    • 07 · Distributions
    • 08 · Relationships + time
    • 09 · Midterm exam
    • 10 · Career studio
    • 11 · Intro to Gen AI
    • 12 · Working with AI
    • 13 · Responsible AI
    • 14 · Tell the story
    • 15–16 · Present

DANL 101 · Introduction to Data Analytics Instructor: Byeong-Hak Choe SUNY Geneseo · Fall 2026

DANL 101 · Fall 2026 · SUNY Geneseo

Learn to think with data.

Move from sharp questions to credible analysis—with R and visualization first, then generative AI and stories that help people decide.

Start with Week 1 Explore the semester

The course arc

From a good question to a clear data story.

Each part of the course builds on the last. Follow the sequence to see what you will learn—and why it matters.

01Frame · Week 1Analytics questions + workflowAsk answerable questions, identify credible evidence, and understand the analytical process from question to insight.→
02Analyze · Weeks 2–6 · Coming soonBuild and prepare data with RWrite reproducible scripts, summarize data, connect tables, and transform observations for analysis.
03Visualize · Weeks 7–8 · Coming soonSee distributions, relationships, and changeUse ggplot2 to reveal patterns across distributions, relationships, groups, and time.
04Apply · Weeks 9–16 · Coming soonConnect analysis, AI, and storytellingAfter the midterm and career studio, examine generative AI, then turn evidence into a focused group data story.
Dates to keep in view

Plan around the moments that shape the semester.

Aug 26First course meeting
Oct 10–13Fall break
Oct 19Midterm exam
Dec 2–7Group presentations
Everything in reach

Open the right workspace.

Weekly pages tell you what to focus on. These collections keep every published course item easy to find.

Lecture slidesConcepts, examples, live coding, and lecture visuals. ClassworkHands-on practice designed for class sessions. HomeworkAssignment pages and instructions. Submit completed work in Brightspace. BrightspaceSubmissions, grades, announcements, and recordings. Group projectBrowse project topics, supporting datasets, and the storytelling guideline. SyllabusCourse policies, outcomes, assessment, and full details.

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