Data Science
DS 2000: Programming with Data
Lecture - 2 credits
ND
EI
IC
FQ
SI
AD
DD
ER
WF
WD
WI
EX
CE
- Introduces programming for data and information science through case studies in business, sports, education, social science, economics, and the natural world.
- Presents key concepts in programming, data structures, and data analysis through Python and Excel.
- Integrates the use of data analytics libraries and tools.
- Surveys techniques for acquiring and programmatically integrating data from different sources.
- Explains the data analytics pipeline and how to apply programming at each stage.
- Discusses the programmatic retrieval of data from application programming interfaces (APIs) and from databases.
- Introduces predictive analytics for forecasting and classification.
- Demonstrates the limitations of statistical techniques.
Introduces programming for data and information science through case studies in business, sports, education, social science, economics, and the natural world. Show more.
Co-requisites