Title Text

 

University of Delaware

Department of Physics and Astronomy

 

federica bianco

Biden School of Public Policy and Administration

Data  Science Institute

 

Rubin Observatory Construction Project - Deputy Project Scientist

 

Rubin Observatory Construction Project - Deputy Project Scientist

Rubin Science Collaborations - Coordinator                           

This is a living land acknowledgement developed in consultation with tribal leadership of Poutaxet, what is now known as the “Delaware Bay,” including: the Lenape Indian Tribe of Delaware, the Nanticoke Indian Tribe, and the Nanticoke Lenni-Lenape Tribal Nation in 2021. We thank these leaders for their generosity.

The University of Delaware occupies lands vital to the web of life for Lenni Lenape and Nanticoke, who share their ancestry, history, and future in this region. UD has financially benefited from this regional occupation as well as from Indigenous territories that were expropriated through the United States land grant system. European colonizers and later the United States forced Nanticoke and Lenni Lenape westward and northward, where they formed nations in present-day Oklahoma, Wisconsin, and Ontario, Canada. Others never left their homelands or returned from exile when they could. We express our appreciation for ongoing Indigenous stewardship of the ecologies and traditions of this region. While the harms to Indigenous people and their homelands are beyond repair, we commit to building right relationships going forward by collaborating with tribal leadership on actionable institutional steps.

Principles of Urban Informatics

large class (2x50)

diverse background - Master level

2015-2019
2019-now

2019-now

2019-now

2021&23

 

ML

PNS

DS

PS

Principles of Urban Informatics

large class (2x50)

diverse background - Master level

Data Science for Physical Scientists 

small class (20)

undergrad+grad - Natural Sciences

2015-2019
2019-now

2019-now

2019-now

2021&23

 

ML

PNS

DS

PS

Principles of Urban Informatics

large class (2x50)

diverse background - Master level

Data Science for Physical Scientists 

small class (20)

undergrad+grad - Natural Sciences

 Machine Learning for Time Series Analysis

small class (20)

undergrad+grad - Natural Sciences

2015-2019
2019-now

2019-now

2019-now

2021&23

 

ML

PNS

DS

PS

Principles of Urban Informatics

large class (2x50)

diverse background - Master level

 Machine Learning for Time Series Analysis

small class (20)

undergrad+grad - Natural Sciences

2015-2019
2019-now

2019-now

2019-now

2021&23

 

ML

PNS

DS

PS

Data Science for Physical Scientists 

small class (20)

undergrad+grad - Natural Sciences

2015-2019
2019-now

2019-now

2019-now

2021&23

 

Principles of Urban Informatics

large class (2x50)

diverse background - Master level

exporting these modules:

 Machine Learning for Natural Scientists

small class (20)

Grads - University of Parma Italy

 Machine Learning for Time Series Analysis

small class (20)

grad - Natural Sciences

ML

PNS

DS

PS

Data Science for Physical Scientists 

small class (20)

undergrad+grad - Natural Sciences

absolute code novices => proficient hackers

data enthusiasts => domain experts

used to structured homework => experience with open investigation

no functional coding => coding for research

domain experience

minimum coding background

little experience w quantitative inference

not accustomed to participatory work

Principles of Urban Informatics

large class (2x50)

diverse background - Master level

Data Science for Physical Scientists 

small class (20)

undergrad+grad - Natural Sciences

 Machine Learning for Time Series Analysis

small class (20)

grad - Natural Sciences

exporting these modules:

 Machine Learning for Natural Scientists

small class (20)

Grads - University of Parma Italy

Data Science provides an opportunity for inclusion in STEM

Including students from population traditionally withheld from STEM

Including STEM newcomers

Introducing students to research methods

Validating Student's Background, Experience, Domain knowledge, Creativity

@fedhere

Recipe:

  • Real Data from Real Problems
  • Collaborative project-based work
  • Free access, industry-ready  tools
  • On-going discussions of DS ethics
  • Discussion-based classroom elements and live coding by the students

harder to achieve

equalizing technology access:

Slack (or discourse), GitHub, GoogleColab, tableau, (authorea, carto), Python

validating everyone's background

(assigned roles: data steward, domain expert, methodology design lead)

real problems from the literature (scientific or public access work, including blogs, medium posts)

@fedhere

students unpack ethical aspects of each project

Data Ethics is now a core course of the ​UD MSDS

Grading

Grading:  while I talk a lot about coding practices, the grade is always only based on the analysis, not the code:  

(1) are the figure telling the story and telling it correctly

(2) figure captions - are the figures interpreted correctly

(3) reproducibility: does the code run

  • Project-based includes a with 1-1 interview

@fedhere

SLIDES

ML

PNS

DS

PS

github.com/fedhere/MLTSA22_FBianco

(ongoing, some material hidden)

Thank you!

Federica B. Bianco

University of Delaware

Physics and Astronomy 

Biden School of Public Policy and Administration

Data Science Institute

NYU Center for Urban Science and Progress

please email me if you have questions! fbianco@udel.edu

@fedhere

Inclusive Data Science Pedagogy Across Domains and Student Populations

By federica bianco

Inclusive Data Science Pedagogy Across Domains and Student Populations

  • 721