Datasets are used for both instruction and projects (see the projects page).  Datasets have been selected using the following criteria as much as possible: 

1. 1. Is real-world data, publicly available, at no cost

   2. Can be used to develop student data and AI skills that are useful in a business context

   3. Data exploration can be used to tell a compelling story

   4. Has some interest or relevance.

Datasets

Generally dataset size is the number of rows, and features are columns

1. Chicago Health Atlas Data, 2005-2011

Snapshot: a publicly available resource providing comprehensive health-related data across Chicago's community areas, encompassing over 160 public health indicators.
Size:  78 Chicago Community Areas (rows), each with  ~60 extracted factors (columns)
Features (samples): Per Capita Income, % Unemployment, % Below Poverty, Crowded Housing, Dependents, No HS Diploma, Birth Rate, Teen Birth Rate, Low Birth Weight, Preterm Births, Lung Cancer, Female Breast Cancer, Male Prostate Cancer, Diabetes, Stroke, Tuberculosis
Uses: predictive modeling of factors contributing to "community health" categories such as income, crime, cancer,  and crowded housing.

Potential Business Problems:
1. Where should a hospital or clinic open a new branch to maximize community impact?
3. How can insurance companies adjust premiums based on population-level risk?

2. Lending Club private loan applications

Snapshot: contains comprehensive loan data from Lending Club, an online marketplace bank that connects borrowers with investors, including borrower information, loan terms, and repayment status.
Uses:  modeling  of  factors that contribute to  high, or low,  quality  loans and application of insights for ML-based predictive modeling.
Size: ~500K loan applications (rows)
Features: 131 features including Credit scores, loan amount, debt-to-income ratio, interest rate, loan purpose, job title
Business Scenario:
1. Can we improve an existing ML model to better predict whether a loan will be paid or charged off?
2. Does an ML model that more accurately predicts whether a loan is repaid or not actually increase the profits of the bank?

3. National Health and Nutrition Examination Survey (NHANES)

Snapshot: Random samples from the original 100K records from the 2017-2018 Pre-Pandemic NHANES dataset.
Uses:  Analysis of relationships between health factors.
Size: 9,828 individuals (rows), each with 17 features (columns)
Features: Time_In_US, Marital Status, Education Level, Born_In_Country, Poverty, Sex, Age, Race, Weight, Waist, Height, BMI, Triglycerides_mol, Sodium, Cholest, Glucose, Iron, Triglycerides.
Potential Business Problems: 

What customer characteristics could be used to identify candidates for preventive health care?

4. Geographic Location Data

The following five datasets can be used together to analyze location-related questions.

4. 1. 1. US Counties 

Snapshot:  US county-level data across a broad range of  features, plus several other city-related datasets
Uses:  Comparing geographic locations
Size: 3,143 US Counties (rows) each with 732 features (columns)
Features: Name, state, area, latitude/longitude, precipitation, temperature, race percentages, age percentages, male/female number, population, prominent causes of death, income, labor, causes of death, politics, education, cost of living, poverty rate, health, industries, zip codes.

4. 1. 500_Cities_2019 

Snapshot:  Health data from the CDC for the largest 500 cities in the country.
Size: 500 US cities (rows) each with location, population, and 28 health-related features (columns)
Features:  See the dataset Data Dictionary tab for more information.
state, name, latitude, longitude, Fed place number,  population. 
Then the following features are percentages: access to insurance, arthritis, binge drinking, high blood pressure, blood pressure meds, cancer, asthma, coronary heart disease, routine check-up, cholesterol screening, colorectal cancer screening, copd pulmonary disease, older men up-to-date, older women up-to-date, smoking, dental visit, diabetes, high cholesterol, kidney disease, lack of leisure physical activity, mammogram, mental health, obesity, pap smear for women, physical distress, short sleep, stroke, teeth lost.

4. 3. Cost_of_Living_Index

Snapshot:  Cost of living index from AdvisorSmith
Size: 511 US cities (rows) each with 3 features (columns)
Features:  City, State, Cost of living index
This is a tool that analyzes the expenses required to maintain a standard of living across various U.S. cities and states. It uses a base of 100 representing the national average, with higher numbers indicating a higher cost of living. The weighted index is comprised of housing (23.2%), consumer spending (22.3%), transportation (18.6%), food (16.1%), utilities (10.1%), and healthcare (9.6%).

4. 4. Income_by_City

Snapshot: Average income by city, along with land and water areas.
Size: 32,526 US cities (rows) each with 19 features (columns)
Features (samples):  City, county, state, zip code, area code, land area, water area, latitude, longitude, household income 

4. 5. County Risks

Snapshot:  Risk measurements by county, from FEMA
Size: 3,231 Counties (rows) each with 465 features (columns)
Features (samples):  Avalanche, coastal flooding, cold waves, drought, earthquake, hail, heat wave, hurricane, ice storm, landslide, lightning, river flooding, strong wind, tornado, tsunami, volcanic activity, wildfire, winter weather.  Along with these is the expected annual loss due to these categories.

Potential Business Problem: 

The financial services company you work for is expanding and wants to open new offices in desirable parts of the country.   Extract, merge, transform, and analyze datasets, coming up with a rank-ordered list of most desirable cities, along with a set of hypotheses and questions that have value for future exploration.

5. UIC course grades distribution Fall 2004 through Fall 2025

Snapshot:
Size: 105,103 courses (rows), each representing a single UIC course offered
Features: Year, Semester, Subject (e.g. CS), Number, Title, Dept, # of each: (A,B,C,D,F,W), Instructor name, # students.
See the  column descriptions  page
Potential Business Problems:
1. Are there courses in a Department that are stumbling blocks for students?
2.  For a college, is there a faculty member who is an outlier in terms of grading?

6. Chicago Crime Data

Snapshot: provides detailed crime incident reports, excluding murders, from 2001 to the present, updated daily from the Chicago Police Department's CLEAR system.
Size: ~250K rows per year, each one representing a crime
Features: ID, Date, Year, Type, FBI Code, Beat (area), District, Ward, Community Area, Arrest (binary), Domestic (binary)
Potential Business Problems:
1. How can realtors and property buyers evaluate neighborhood safety?
2.  Is gentrification correlating with shifts in crime reporting or policing?

Other Datasets

1. CDC: National Immunization Survey Data data dictionary, context
   Snapshot: includes estimates of vaccination coverage rates for U.S. children and for U.S. adolescents.
   Size: ~43K rows (2023), with 676 features for each row
   Features: (~600 columns from vaccination survey, for example: ... HPVI_ANY (number of HPV Vaccination Shots), Sex, Poverty Status, WELLCHILD (Did teen receive an 11–12 year old well-child exam or check-up), etc.
   Potential Bussiness Problems:
   1. Which populations are least likely to be vaccinated, and why?
   2. How can government campaigns improve HPV or flu vaccination rates?