DANL 101
  • Brightspace
  • Materials
    • Lecture Slides
    • Classwork
    • Homework
    • Exams
  • Project
    • Guideline
    • Topics

  • Start Here
    • Home
    • Semester map
    • Syllabus
  • Weekly Roadmap
    • 01 · Analytics workflow
    • 02 · DANL thinking + tools
    • 03 · R workflow + foundations
    • 04 · R fundamentals
    • 05 · Descriptive Statistics
    • 06 · Reading + transforming data
    • 07 · Big data + databases
    • 08 · Databases + data infrastructure
    • 09 · Midterm + Visualization
    • 10 · Visualization: Distributions
    • 11 · Visualization: Relationships + time
    • 12 · Intro to Gen AI
    • 13 · Working with AI
    • 14 · Project studio
    • 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 6 Homework 2Due: Oct 9, 11:59 PM

Week 06 · Sep 28–Oct 2

This week’s materials

Reading and Transforming Data with R

Lecture 5Reading and Transforming Data with R Classwork 5Finding and Copying an Absolute Pathname
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. Group projectBrowse project topics, supporting datasets, and the storytelling guideline. Semester mapSee the week-by-week course path, topics, and major dates. SyllabusCourse policies, outcomes, assessment, and full details.

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
Semester map

From analytics thinking to data-informed decisions.

Prepare data and study databases before the October 19 midterm, then explore visualization for three weeks and generative AI for two weeks before project work and presentations.

01Frame · Weeks 1–2Analytics questions + decision toolsTurn decisions into answerable questions, evaluate evidence, and use dashboards and analytics tools thoughtfully.→ 02Build · Weeks 3–4R foundations + statisticsWork with objects, vectors, data frames, and functions, then summarize center, spread, and distributions.→ 03Prepare · Weeks 5–8Statistics, transformation + databasesSummarize data, practice dplyr, and use Lecture 6 to understand data types, ETL, relational tables, joins, and modern data infrastructure.→
04Assess + visualize · Weeks 9–11 · Coming soonMidterm + data visualizationTake the midterm on October 19, then build charts for distributions, relationships, and time trends.
05Explore AI · Weeks 12–13 · Coming soonGenerative AI + responsible useStudy capabilities and limits, practice prompting and iteration, and verify outputs while considering disclosure, bias, and privacy.
06Apply + present · Weeks 14–16 · Coming soonProject studio + presentationsCheck the group project’s data and code, refine findings, rehearse, and present the completed analysis.
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