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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.
10 spots per session maximum — 9 already taken
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30 free minutes with a training advisor — no commitment.
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Don't let this gap widen
Without mastery of LangSmith Tracing, advanced LangChain developers spend 3x longer debugging opaque LLM chains, averaging 30 hours weekly on elusive errors.
This inefficiency costs teams $75,000 per developer annually in lost productivity and delayed deployments.
70% of production incidents in LangChain applications stem from untraced execution paths, exposing companies to compliance violations, customer churn, and multimillion-dollar revenue hits.
Every month without tracing expertise, these risks compound, threatening careers and business viability.
The Training in LangSmith Tracing 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 in LangSmith Tracing 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 in LangSmith Tracing 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.
Discover LangSmith, a powerful tool for tracing LLMs. Install LangSmith CLI. Create a free account. Configure API keys. Enable automatic tracing. Launch your first LangChain chain. Visualize traces in the dashboard. Identify latencies. Analyze inputs and outputs. Explore individual runs. Manage basic datasets. Share traces with the team. Secure project access. Integrate custom logging. Test tracing callbacks. Resolve common errors. Practice simple exercises. Master tracing basics. Boost development productivity. Optimize AI apps from day 1.
Dive into deep debugging. Use trace filters. Segment by custom tags. Trace complex agents. Debug RAG pipelines. Analyze token costs. Monitor embeddings. Manage parallel multi-runs. Integrate LangSmith Python SDK. Customize trace metadata. Automate trace tests. Visualize dependency graphs. Identify performance bottlenecks. Resolve LLM hallucinations. Test iterative prompts. Share insights with the team. Export trace data. Integrate into CI/CD pipelines. Scale tracing for production. Practice real-world cases. Master advanced tools. Accelerate AI developments.
Transition to production tracing. Configure safety guards. Monitor production in real-time. Set up automatic anomaly alerts. Optimize tracing costs. Migrate legacy chains. Integrate with observability stacks. Analyze long-term trends. Create custom dashboards. Automate LLM evaluations. Manage prompt versioning. Scale for multi-tenant environments. Secure sensitive data. Perform regular trace backups. Migrate to LangGraph. Test application resilience. Benchmark LLM models. Share best practices. Deploy live monitoring. Finalize personal projects. Validate final skills. Become a LangSmith expert.
Target audience
Advanced LangChain developers
Prerequisites
Python and LangChain basics required
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