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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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The DSPy Training - Programming LLMs Optimally 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 DSPy Training - Programming LLMs Optimally 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 DSPy Training - Programming LLMs Optimally 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.
Quick installation of the DSPy environment and connection to LLM models like GPT or Llama, definition of signatures to structure classification and text generation prompts, creation of basic modules applied to concrete business cases, practical exercises in automatic optimization with BootstrapFewShot, iteration on reasoning pipelines to maximize accuracy and efficiency, completion of a red thread project with metric evaluation and immediately deployable deliverables, personalized feedback from the trainer to anchor professional skills.
Target audience
Python developers, data scientists, and beginner AI engineers in LLM frameworks seeking professional skill enhancement
Prerequisites
Solid Python fundamentals and introductory knowledge of LLM language models
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