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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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Don't let this gap widen
Without mastering Groq API integration, production AI systems suffer latency spikes exceeding 10x expected speeds, wasting 35% more compute resources on average.
In enterprise settings, 72% of deployment failures trace back to improper API handling, incurring $150,000 in downtime and rework costs per incident.
Unaddressed skill gaps expose companies to lost market share as rivals deploy ultra-fast inference, stalling revenue-generating applications and hindering team promotions.
Every month without expertise, cloud bills inflate by 40%, compounding into millions in avoidable losses.
The Training Groq API - Integrating Ultra-Fast AI in Production training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training Groq API - Integrating Ultra-Fast AI in Production training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training Groq API - Integrating Ultra-Fast AI in Production training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Groq API key configuration. Understanding LPU hardware for speed. Token management and rate limits. Secure OAuth authentication. Exercises: Python Streamlit project setup. Integration of first Mixtral models. Real enterprise cases: fast chatbots. Setting up end-to-end AI project. Debugging common errors. Optimizing first requests. Practice on real datasets. (112 words)
Exploring models: Llama3, Gemma2, Mistral. Advanced prompting techniques: chain-of-thought, few-shot. Native Groq tool calling. Structured JSON mode. Professional exercises: automated code generation. Implementing basic RAG. End-to-end project: enterprise AI assistant. Latency evaluation vs OpenAI. Performance benchmarks. Managing long contexts. Business use cases: data analysis. (98 words)
Implementing real-time streaming responses. WebSockets for reactive UIs. State management with LangChain Groq. Multi-turn conversational sessions. Exercises: live streaming chatbot. FastAPI backend integration. End-to-end project: interactive AI dashboard. Robust error handling with retries. API cost monitoring. Real cases: AI customer support. Scalability with parallel threads. Practice deploying on Vercel. (92 words)
Connections to vector databases Pinecone, Weaviate. Full RAG with embeddings. Hybrids Groq + HuggingFace. External tools via function calling. Security: rate limiting, PII masking. Exercises: enterprise semantic search. End-to-end project: internal docs RAG app. CI/CD with GitHub Actions. Prometheus monitoring. Business cases: workflow automation. Batching optimization. GDPR compliance audit. (96 words)
Docker Kubernetes deployment on AWS/GCP. Autoscaling Groq workloads. Prompt fine-tuning A/B testing. Cost optimization with caching. Observability monitoring with Sentry. Exercises: production-ready scalable app. Presentation of complete end-to-end project. AI DevOps best practices. Legacy API migration. Groq evolution roadmap. Professional skills certifications. Q&A on real enterprise cases. (89 words)
Target audience
AI Developers, ML Engineers, Software Architects for upskilling in Groq API in enterprise settings
Prerequisites
Advanced Python mastery, REST/GraphQL APIs, LLMs such as Llama or GPT
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