ChatGPT Prompt Engineering for Developers
E824070
ChatGPT Prompt Engineering for Developers is an online course by DeepLearning.AI that teaches developers practical techniques for crafting effective prompts to build powerful applications with large language models.
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
developer training course
ⓘ
online course ⓘ |
| accessMode | self-paced ⓘ |
| creator | DeepLearning.AI NERFINISHED ⓘ |
| deliveryMode | online ⓘ |
| focusesOn |
ChatGPT
NERFINISHED
ⓘ
large language models ⓘ prompt engineering ⓘ |
| goal |
help developers build powerful LLM applications
ⓘ
improve prompt quality and reliability ⓘ |
| hasComponent |
coding examples
ⓘ
hands-on exercises ⓘ video lectures ⓘ |
| hasFormat | browser-based learning ⓘ |
| intendedOutcome |
enable students to design robust prompts
ⓘ
enable students to integrate LLMs into applications ⓘ |
| language | English ⓘ |
| name | ChatGPT Prompt Engineering for Developers NERFINISHED ⓘ |
| offeredBy | DeepLearning.AI platform NERFINISHED ⓘ |
| offeringType | short course ⓘ |
| prerequisiteKnowledge |
basic programming skills
ⓘ
familiarity with Python (typical) ⓘ |
| provider | DeepLearning.AI NERFINISHED ⓘ |
| relatedTo |
AI application development
ⓘ
applied generative AI ⓘ software engineering ⓘ |
| subjectArea |
artificial intelligence
ⓘ
machine learning ⓘ natural language processing ⓘ |
| targetAudience |
engineers building LLM applications
ⓘ
software developers ⓘ |
| teaches |
how to build applications with large language models
ⓘ
how to control LLM behavior with prompts ⓘ how to design prompts for different tasks ⓘ how to structure system and user messages ⓘ how to write effective prompts for LLMs ⓘ iterative prompt development ⓘ practical techniques for crafting prompts ⓘ prompt debugging ⓘ prompt patterns ⓘ |
| typicalUseCase |
building chatbots
ⓘ
building code-assistance tools ⓘ building content generation tools ⓘ |
| uses |
ChatGPT API
NERFINISHED
ⓘ
OpenAI models NERFINISHED ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.