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.
All labels observed (1)
| Label | Occurrences |
|---|---|
| ChatGPT Prompt Engineering for Developers canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9838326 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ChatGPT Prompt Engineering for Developers Context triple: [Deeplearning.ai, hasNotableCourse, ChatGPT Prompt Engineering for Developers]
-
A.
ChatGPT Enterprise
ChatGPT Enterprise is OpenAI’s business-grade version of ChatGPT, offering enhanced security, admin controls, and scalable access to advanced AI capabilities for organizations.
-
B.
ChatGPT
ChatGPT is an advanced conversational AI model developed by OpenAI that can understand and generate human-like text across a wide range of topics and tasks.
-
C.
OpenAI Codex API
The OpenAI Codex API is a cloud-based interface that lets developers integrate Codex’s natural-language-to-code generation and code understanding capabilities into their own applications and tools.
-
D.
OpenAI API platform
The OpenAI API platform is a cloud-based service that provides developers with programmatic access to OpenAI’s language, code, and other AI models for integration into applications and workflows.
-
E.
GPT
GPT is a family of large language models developed by OpenAI that can understand and generate human-like text for a wide range of tasks.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ChatGPT Prompt Engineering for Developers Target entity description: 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.
-
A.
ChatGPT Enterprise
ChatGPT Enterprise is OpenAI’s business-grade version of ChatGPT, offering enhanced security, admin controls, and scalable access to advanced AI capabilities for organizations.
-
B.
ChatGPT
ChatGPT is an advanced conversational AI model developed by OpenAI that can understand and generate human-like text across a wide range of topics and tasks.
-
C.
OpenAI Codex API
The OpenAI Codex API is a cloud-based interface that lets developers integrate Codex’s natural-language-to-code generation and code understanding capabilities into their own applications and tools.
-
D.
OpenAI API platform
The OpenAI API platform is a cloud-based service that provides developers with programmatic access to OpenAI’s language, code, and other AI models for integration into applications and workflows.
-
E.
GPT
GPT is a family of large language models developed by OpenAI that can understand and generate human-like text for a wide range of tasks.
- F. None of above. chosen
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 ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: ChatGPT Prompt Engineering for Developers Description of subject: 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.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.