Course overview
Principles and practices for integrating AI into day-to-day development: matching models to tasks, prompt engineering for debugging and documentation, building robust AI workflows and safeguards for responsible coding.
Overview of the AI-assisted coding paradigm, how to align models with tasks, classify AI workloads and core prompt engineering concepts.
Advanced prompt engineering methods tailored for coding: prompts for efficient debugging, crafting role definitions and using AI to generate code documentation.
Designing AI workflows for code: choosing the right AI tool per job, understanding assistant cost trade-offs and reasoning model trade-offs, and implementing operational safeguards.
Skills and topics covered
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