SYSEN 5460 Data Science for Socio-Technical Systems: Decision-Making and Data Communication at Scale

Course description

Modern systems frequently use databases to record, share, and route big data from socio-technical systems, including electrical grids, airlines, public transit, banking, security, and software systems, among others. This course trains engineers to query, visualize, and communicate big data at scale, specifically in socio-technical systems. Training includes building and using relational databases, data visualization, and creating systems for data communication using dashboards. Several formats are explored, including time-series, geospatial, and network data. Participants will learn to analyze systems using database techniques in an open-source programming language, measure system performance, and communicate findings for non-experts, emphasizing data-driven decision-making for public-facing technologies. No prior coding or statistical experience is required; by the course’s end, participants will demonstrate mastery of core techniques for databases, visualization, and dashboards.

Learning outcomes:
+ Analyze Big Datasets and Databases. Participants will use data wrangling techniques and SQL/SQLite to process social-technical systems data at scale, using spatial and network techniques.
+ Make Data-Driven Decisions. This includes the measurement and design of key metrics to enable managers to make data-driven decisions that meet stakeholder needs.
+ Communicate and Visualize Data Effectively. Participants will learn methods for advanced data communication techniques and their tradeoffs when communicating findings to the public.
+ Build Dashboard Interfaces for Databases. Participants will learn how to systematically architect and build dashboard systems to interface with databases, from mapping their process to implementation and testing.
+ Evaluate Socio-Technical Data. Skills include drawing inferences from big data over time, spatial data, and network data.

Prerequisites

Prior statistics coursework or coding coursework may be helpful, but not required.

Previously offered classes