EGR 105L
Computing for Engineers
David Andrew Ward
Description from DukeHub
Introduction to computational thinking, modeling, and programming to solve authentic engineering problems. Students will learn to visualize data; as well as a design, test, and deliver solutions with an industry-standard computational tools. Topics include: devising an algorithm and writing, documenting, testing, and debugging code. Course emphasizes both strategic collaboration and individual resourcefulness in seeking solutions. Primary computational language used in this class is Python. No prior knowledge of computer programming is required. Open to Pratt first-year students. Others, by permission only.
Skills
- programmingdescription: "programming" and 4 more
- lab workhas a lab component
- data and statisticsAI review: "Students will learn to visualize data"
- designAI review: "design, test, and deliver solutions"
AI-resilient: 2 of 5
- Yes: Physical, lab or field work · "laboratory"
- Yes: Live work with people · "collaboration"
- No: Judgment someone is accountable for
- 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
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