FORMATION IA
Fondamentaux de l'API et de la Console Anthropic
Construisez et déployez des applications basées sur Claude grâce à l'API, la Console et les outils développeurs d'Anthropic.
Ce qu'elle couvre
Cette formation pratique couvre l'ensemble de l'écosystème développeur Anthropic : prise en main de la Console et du Workbench, authentification et appels à l'API Messages, sélection du bon modèle Claude selon la charge de travail, et implémentation de fonctionnalités avancées comme le cache de prompts, l'utilisation d'outils et le streaming. Les participants réalisent des exercices de code concrets en Python et/ou TypeScript. À l'issue de la formation, ils sont capables de concevoir une intégration prête pour la production, d'optimiser coûts et latence, et de diagnostiquer les erreurs API courantes.
À l'issue, vous saurez
- Authenticate to the Anthropic API and send correctly structured Messages API requests from a local or cloud environment
- Choose the appropriate Claude model variant for a given workload based on latency, cost, and capability requirements
- Implement prompt caching to reduce token costs by up to 90% on repeated context
- Define, call, and handle multi-turn tool-use loops to extend Claude with external functions and data sources
- Stream responses and handle partial events gracefully in a production Python or TypeScript service
- Diagnose and remediate common API errors including rate limits, malformed requests, and context-window overflows
Sujets abordés
- Anthropic Console and Workbench navigation and prompt prototyping
- Messages API structure: roles, content blocks, system prompts, and parameters
- Model selection: Claude 3 Haiku vs Sonnet vs Opus trade-offs for latency, cost, and capability
- Prompt caching: mechanics, TTL, cache-hit optimisation, and cost savings calculation
- Tool use (function calling): defining tools, handling tool_use blocks, and multi-turn tool loops
- Streaming responses with server-sent events in Python and TypeScript SDKs
- Error handling, retries, and rate-limit management in production
- Cost estimation, token counting, and API budget governance
Modalité
Delivered as a 2-day intensive bootcamp (in-person or live virtual). Day 1 focuses on Console exploration and core API mechanics; Day 2 covers advanced features and a capstone integration project. Approximately 60% hands-on coding, 40% instruction. Participants need a laptop with Python 3.10+ or Node 18+ and a valid Anthropic API key (trial credits sufficient). Materials include slide deck, Jupyter notebooks, and a private GitHub repo with starter code and solutions.
Ce qui fait que ça marche
- Starting with a real internal use case as the capstone project so participants apply concepts immediately
- Establishing a shared API key management and cost-monitoring policy before the training ends
- Pairing engineers with a designated AI lead who reviews integrations one week post-training
- Using the Anthropic Workbench actively during development to iterate on prompts before hardcoding them
Erreurs fréquentes
- Passing the entire document corpus in every request instead of leveraging prompt caching, leading to unnecessary token spend
- Ignoring model-tier trade-offs and defaulting to the most capable (and expensive) model for every task
- Implementing tool use without validating tool_result blocks, causing silent failures in multi-turn loops
- Not implementing exponential back-off for rate-limit errors, resulting in brittle production integrations
Quand NE PAS suivre cette formation
A non-technical team (e.g., marketing or HR) that only needs to use Claude via a SaaS front-end and will never write API code — this training is overly technical and a prompt-engineering or tool-adoption workshop would serve them better.
Fournisseurs à considérer
Sources
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