Course Syllabus

V415 Data Science in Public & Environmental Affairs

Indiana University – O'Neill School of Public and Environmental Affairs

Semester: Fall 2026

Credits: 3

Delivery Mode: In-person (with Canvas-supported instructional activities)

Instructor Information

Instructor: Professor Karen Sowon

Office Hours: Posted on Canvas

Contact: Posted on Canvas

Note: In accordance with Indiana University policy and Indiana state law, this syllabus is publicly viewable. Detailed assignment instructions, submission links, rubrics, instructor contact information, and weekly course materials are provided within Canvas.

Course Description

This course introduces students to the principles and practice of data science for public and environmental decision-making. Rather than focusing on advanced programming or mathematics, the course emphasizes asking meaningful questions, finding and evaluating data, preparing data for analysis, creating effective visualizations, and communicating evidence-based recommendations.

Students learn through a combination of discussions, hands-on studio activities, resource guides, and a semester-long consulting engagement using authentic public datasets. Artificial intelligence (AI) is integrated throughout the course as a professional tool while emphasizing responsible and ethical use.

No prior programming or data science experience is required.

Learning Outcomes

By the end of this course, students will be able to:

  • Formulate analytical questions that can be investigated using data.
  • Locate and evaluate appropriate public and environmental data sources.
  • Assess the trustworthiness, quality, and fitness of data for decision-making.
  • Prepare datasets for analysis using professional workflows.
  • Create effective data visualizations and dashboards.
  • Use Excel, Tableau, Google Colab (Python), and AI tools to support analysis.
  • Communicate evidence-based recommendations to non-technical audiences.
  • Apply professional judgment throughout the data science process.

Required Technologies

Students should have regular access to:

  • A laptop computer
  • Reliable internet access
  • Canvas (IU Learning Management System)
  • Microsoft Excel (IU Microsoft 365)
  • Tableau Public/Desktop
  • Google Colab
  • ChatGPT (free or paid version)

Additional software and online resources will be introduced throughout the semester.

Accessibility and Inclusive Learning

Indiana University is committed to providing accessible learning environments. Course materials are designed to meet university accessibility standards whenever possible. Students requiring accommodations should contact Disability Services for Students (DSS) as early as possible. Once accommodations have been approved, please notify the instructor through official DSS channels.

Artificial Intelligence

Responsible Use of AI

Artificial intelligence is an expected part of professional data science practice and will be used throughout this course.

Students are encouraged to use AI tools to:

  • brainstorm ideas,
  • explain concepts,
  • support coding,
  • assist with data preparation,
  • improve communication.

Students remain responsible for verifying the accuracy of AI-generated content and for all work submitted.

When AI has made a meaningful contribution to an assignment, students should briefly acknowledge how it was used.

Use of AI during quizzes or other assessments where prohibited is considered academic misconduct.

Attendance and Professional Engagement

Because this course is organized around discussions, consulting activities, and studio sessions, regular attendance and participation are expected.

Professional engagement includes:

  • arriving prepared,
  • contributing to discussions,
  • participating in studio activities,
  • collaborating respectfully,
  • supporting teammates.

Students who miss more than three class meetings without prior communication or documented extenuating circumstances may receive a reduction in their Professional Engagement grade.

Detailed expectations and grading criteria are available in Canvas.

Assessment

Students will be assessed through applied work completed throughout the semester.

Component Weight
Professional Engagement 15%
Weekly Assignments & Studio Deliverables 25%
Portfolio Milestones 25%
Final Consulting Engagement 35%

There are no traditional midterm or final examinations.

Late Work

Assignments submitted after the deadline receive a 10% deduction per calendar day unless prior arrangements have been made because of documented extenuating circumstances.

Because portfolio milestones build on one another, late submissions may also affect instructor feedback and subsequent assignments.

Copyright and Course Materials

Course materials are provided for enrolled students only and remain the intellectual property of the instructor and Indiana University. Course materials may not be distributed, sold, reposted, or uploaded to external AI systems without written permission from the instructor.

Respectful Learning Environment

Students are expected to contribute to an inclusive and respectful learning environment. Diverse viewpoints are encouraged. Harassment, discrimination, or disruptive behavior—whether in person or online—will not be tolerated.

Health, Wellness, and Title IX

Indiana University provides a variety of resources to support student wellbeing, including Counseling and Psychological Services (CAPS), the Student Advocates Office, and Title IX resources. Faculty are required to report disclosures of sexual misconduct in accordance with university policy.

Course Schedule (Public Summary)

The course follows a progressive semester-long consulting model organized around the theme:

From Data to Decisions

Major topics include:

  • Asking good analytical questions
  • Finding and evaluating public data
  • Preparing data for analysis
  • Data visualization and storytelling
  • Exploratory data analysis
  • AI-assisted data science
  • Dashboards and communication
  • Responsible AI and data ethics
  • Evidence-based recommendations
  • Final consulting engagement

A detailed weekly schedule, assignment deadlines, readings, Resource Guides, and instructional materials are available in Canvas under Modules.

The instructor reserves the right to make reasonable adjustments to the schedule to support student learning.