ECE 785D
Data Engineering
Javier Pastorino
Description from DukeHub
This course introduces the foundations of data engineering and data governance, integrating them with DataOps, and modern data storage systems. It covers core data governance activities, including requirements gathering, data cleansing, extraction, transformation, and loading (ETL). The course introduces networking and data storage concepts beyond individual files, encompassing relational and NoSQL data models deployed on single-server systems, on-premises clusters, and cloud-based platforms. DataOps best practices are applied to design, orchestrate, and operate data pipelines that serve as the backbone of machine learning workflows.
Skills
- programmingdepartment: ECE
- policy and lawdescription: "governance" and 1 more
- data and statisticsAI review: "data cleansing, extraction, transformation, and loading (ETL)"
AI-resilient: 1 of 5
- No: Physical, lab or field work
- No: Live work with people
- Yes: Judgment someone is accountable for · "governance"
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
More in ECE
- Fundamentals of Electrical and Computer Engineering ECE 110L
- Fundamentals of Electrical and Computer Engineering - Lab ECE 110L9
- Introduction to Microelectronic Devices and Circuits ECE 230L
- Introduction to Microelectronic Devices and Circuits-Lab ECE 230L9
- Fields and Waves: Fundamentals of Information Propagation ECE 270DL
- Fields and Waves: Fundamentals of Information Propagation (Lab) ECE 270L9