Difference between revisions of "Human Centered Data Science (Fall 2019)/Schedule"

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Revision as of 22:07, 4 September 2019

This page is a work in progress.


Week 1: September 26

Day 1 plan

Introduction to Human Centered Data Science
What is data science? What is human centered? What is human centered data science?
Assignments due
Agenda

HCDS (Fall 2019)/Day 1 plan

Readings assigned
Homework assigned
  • Reading reflection
  • A1: Data curation
Resources




Week 2: October 3

Day 2 plan


Reproducibility and Accountability
data curation, preservation, documentation, and archiving; best practices for open scientific research
Assignments due
  • Week 1 reading reflection
  • A1: Data curation
Agenda

HCDS (Fall 2019)/Day 2 plan

Readings assigned
Homework assigned
  • Reading reflection
  • A2: Bias in data
Resources


Assignment 1 Data curation resources





Week 3: October 10

Day 3 plan

Interrogating datasets
causes and consequences of bias in data; best practices for selecting, describing, and implementing training data
Assignments due
  • Reading reflection
Agenda

HCDS (Fall 2019)/Day 3 plan

Readings assigned (Read both, reflect on one)
Homework assigned
  • Reading reflection
Resources




Week 4: October 17

Day 4 plan


Introduction to mixed-methods research
Big data vs thick data; integrating qualitative research methods into data science practice; crowdsourcing


Assignments due
  • Reading reflection
  • A2: Bias in data


Agenda

HCDS (Fall 2019)/Day 4 plan


Readings assigned (Read both, reflect on one)


Homework assigned


Qualitative research methods resources
Wikipedia gender gap research resources
Crowdwork research resources




Week 5: October 24

Day 5 plan

Ethical considerations
privacy, informed consent and user treatment


Assignments due
  • Week 1 reading reflection
Agenda

HCDS (Fall 2019)/Day 5 plan


Readings assigned


Homework assigned
Resources




Week 6: October 31

Day 6 plan

Interrogating algorithms
algorithmic fairness, transparency, and accountability; methods and contexts for algorithmic audits
Assignments due
Agenda

HCDS (Fall 2019)/Day 6 plan

Readings assigned


Homework assigned
  • Reading reflection


Resources





Week 7: November 7

Day 7 plan

Critical approaches to data science
power, data, and society; ethics of crowdwork


Assignments due
  • Reading reflection
  • A3: Crowdwork ethnography


Agenda

HCDS (Fall 2019)/Day 7 plan

Readings assigned (read both, reflect on one)
Homework assigned


Resources





Week 8: November 14

Day 8 plan

Human-centered algorithm design
algorithmic interpretibility; human-centered methods for designing and evaluating algorithmic systems


Assignments due
  • Reading reflection


Agenda

HCDS (Fall 2019)/Day 8 plan

Readings assigned
Homework assigned
  • Reading reflection
Resources





Week 9: November 21

Day 9 plan

Data science for social good
Community-based and participatory approaches to data science; Using data science for society's benefit
Assignments due
  • Reading reflection
  • A4: Final project plan
Agenda

HCDS (Fall 2019)/Day 9 plan

Readings assigned
Homework assigned
  • Reading reflection
Resources





Week 10: November 28 (No Class Session)

Readings assigned
  • NONE
Homework assigned
  • A5: Final presentation
Resources





Week 11: December 5

Day 11 plan

Final presentations
course wrap up, presentation of student projects


Assignments due
  • A5: Final presentation


Agenda

HCDS (Fall 2019)/Day 11 plan

Readings assigned
  • none!
Homework assigned
  • A6: Final project report (due 12/9 by 11:59pm)
Resources
  • one




Week 12: Finals Week (No Class Session)

  • NO CLASS
  • A6: FINAL PROJECT REPORT DUE BY 5:00PM on Tuesday, December 10
  • LATE PROJECT SUBMISSIONS NOT ACCEPTED.