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IA & Data
Applied Prompt Engineering – Building and Deploying AI Pipelines
2 jour(s) • 14h
Description
This advanced-level training is designed for developers, data analysts, and technical project managers seeking to go beyond basic conversational use of generative AI. It covers the design of complex prompt pipelines, integration via OpenAI and Anthropic APIs, RAG architectures, production evaluation, and securing application usage — delivered over 2 intensive days with 100% hands-on pedagogy.
Learning Objectives
- Call OpenAI and Anthropic APIs in Python with fine-tuning (temperature, top_p, max_tokens, stop sequences, streaming)
- Design structured system prompts, multi-role instructions, and conditional prompt chains
- Build a complete RAG pipeline (embeddings, vectorstore, retrieval, reranking) on a professional document corpus
- Implement an orchestration workflow with LangChain or LlamaIndex including memory, tools, and autonomous agents
- Evaluate response quality in production using RAGAS, LLM-as-judge, and automated regression tests
- Secure an application AI pipeline against prompt injection, context leakage, and sensitive data exposure
- Monitor costs, latency, and quality in production with Langfuse and define alert thresholds
- Deliver a functional AI pipeline prototype that is documented, tested, and ready for code review
Target Audience
Python developers (junior to senior)
Data analysts and data engineers
Technical project managers/architects
DevOps engineers exposed to AI pipelines
Technical consultants for major accounts
Prerequisites
Intermediate proficiency in Python (functions, libraries, virtual environments)
Basic knowledge of REST APIs (HTTP requests, JSON, authentication)
Completion of PE-PRO-200 or equivalent level recommended
Operational Python 3.10+ environment on the workstation
Program Outline
Informations
Duration
2 jour(s)
14h
Tarif
Sur demande
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