Computational Thinking and Programming with AI

Description from DukeHub

We will learn to program effortlessly in Mathematica / Wolfram Language, Python, R, and any other programming language. We will let Large Language Models do most of the programming for us. We will study the best practices in prompt engineering, i.e., formulating the prompts in plain English to get the desired programs. The well-thought-out prompts produce much better results than the vague ones. Thus, learning prompt engineering will sharpen our problem-solving skills. We will watch demonstrations of using AI to solve simple and then increasingly difficult problems. You will develop 6-8 Projects with increasing complexity. The final project involves a 20-minute presentation to the class. Prerequisites: EGR 105L and Math 353 (or equivalents), or graduate student standing.

Skills

• programmingdescription: "python" and 2 more
• ai and machine learningtitle: "ai"
• public speakingAI review: "The final project involves a 20-minute presentation to the class"

AI-resilient: 0 of 5 0/5

• No: Physical, lab or field work
• No: Live work with people
• 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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