Building with LLM APIs
Call language models from your own code: requests, streaming, tools and costs.
30tutors
6teachers
3free to start
$3 to $12per paid lesson
Building with LLM APIs tutors
30 tutors
Becoming an LLM Application Engineer
Becoming an LLM Application Engineer
Learn what LLM application engineers do and build the skills and evidence to move into the role45 lessonsSampleYohannes Tesfaye$8Reliable Document Summarisation PipelinesReliable Document Summarisation Pipelines
Build summarisation that handles long documents, keeps facts straight and can be checked against the source.44 lessonsSampleGreta Lindqvist$7Streaming Responses to Your InterfaceStreaming Responses to Your Interface
Stream model output token by token from the API through your backend to the browser, errors included.43 lessonsSampleGabriela Sousa$6LLM APIs Explained for Product TeamsLLM APIs Explained for Product Teams
Understand what your engineers mean by tokens, context, latency and rate limits, and ask better questions.43 lessonsSampleGabriela Sousa$4Async Python for Many API CallsAsync Python for Many API Calls
Run hundreds of model or web API calls concurrently with asyncio, limits, retries and clean results.41 lessonsSampleFelix Brandt$9Messages, Roles and Conversation StateMessages, Roles and Conversation State
Understand system, user and assistant messages and store conversations correctly in your own app.39 lessonsSampleGabriela Sousa$4Classifying Text with an LLM APIClassifying Text with an LLM API
Sort tickets, reviews or messages into categories with a model, and measure how accurate it really is.39 lessonsSampleGreta Lindqvist$4Images and Documents as Model InputImages and Documents as Model Input
Send photos, screenshots, charts and PDFs to a model and get answers you can check and trust.36 lessonsSampleGreta Lindqvist$5Getting Reliable JSON Out of a ModelGetting Reliable JSON Out of a Model
Get model output your code can parse: schemas, validation, truncation handling and safe retries.32 lessonsSampleGreta Lindqvist$5API Key Safety and Secrets HandlingAPI Key Safety and Secrets Handling
Keep model API keys out of code, repos, browsers and logs, and know exactly what to do if one leaks.32 lessonsSampleFarid HaddadFreePrompt Caching for Lower Cost and LatencyPrompt Caching for Lower Cost and Latency
Structure prompts so repeated prefixes are cached, then measure the savings in cost and response time.28 lessonsSampleFarid Haddad$7Build a Chat Backend That Holds UpBuild a Chat Backend That Holds Up
Design and build a chat backend with auth, storage, streaming, quotas and cost tracking that survives real use.18 lessonsSampleGabriela Sousa$8Teachers who teach Building with LLM APIs
They wrote the lesson plans these tutors follow.
Emeka Nwosu
Search engineer teaching embeddings, chunking, vector and keyword search, and reranking from first principlesembeddings, chunking, vector databases9 tutorsSampleFelix Brandt
Numerical Python and code quality for data and AI projects that have outgrown a single notebookNumPy, pandas, plotting9 tutorsSampleFarid Haddad
Keeps LLM features fast, affordable and available as traffic grows: cost, caching, retries and observabilitytoken counting, cost control, prompt caching9 tutorsSampleGabriela Sousa
Teaches developers and product teams to make their first LLM API calls and design simple apps around themfirst API requests, messages and roles, system prompts9 tutorsSampleGreta Lindqvist
Structured output, tool calling and safe input handling for LLM applications that must behave predictablystructured output and JSON schemas, tool and function calling, image and document input9 tutorsSampleYohannes Tesfaye
Machine learning engineer who runs portfolio reviews and mock interviews for technical AI rolesML engineering interviews, data science interviews, AI product manager interviews9 tutorsSampleMore in Building with AI
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