Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training Gemma - Deploying Generative AI in the Enterprise training are: Expertise in Python, PyTorch, fine-tuning transformers, and managing large datasets. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Gemma - Deploying Generative AI in the Enterprise training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Gemma - Deploying Generative AI in the… | Learni

The story of Learni

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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Methods, approaches, and teaching resources

The Training Gemma - Deploying Generative AI in the Enterprise 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.

Teaching resources provided

To ensure the quality of the Training Gemma - Deploying Generative AI in the Enterprise training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and 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.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training Gemma - Deploying Generative AI in the Enterprise training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

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.

Training objectives

Master the Gemma architecture for professional, certified implementations

Develop skills in advanced fine-tuning of Gemma in enterprise settings

Optimize Gemma model performance for scalable deployments

Implement RAG pipelines with Gemma for business applications

Design autonomous AI agents based on Gemma

Evaluate and secure Gemma solutions in production

Deploy Gemma on cloud and edge infrastructures

Training program

Module 1Gemma Architecture: Dissecting the Model and Initial Fine-Tuning (PyTorch, Hugging Face)

Dive into the deep architecture of Gemma 2B and 7B, analysis of attention layers and advanced tokenization mechanisms, setting up PyTorch and Hugging Face Transformers environments to load pre-trained weights, first fine-tuning exercises on customized enterprise datasets, production of a basic model adapted to a concrete business case with integrated evaluation metrics, immediate feedback to accelerate your professional skills.

Module 2Expert Gemma Fine-Tuning: LoRA, QLoRA, and Memory Optimization (PEFT, bitsandbytes)

Master LoRA and QLoRA techniques to fine-tune Gemma on limited hardware, implementation with the PEFT and bitsandbytes libraries to reduce VRAM usage by up to 70%, practical exercises on multilingual and sector-specific datasets such as finance or healthcare, generation of high-performing customized models, comparison of perplexity and BLEU metrics on your own use cases, preparation of production-ready deliverables to enhance your certified skills.

Module 3RAG Pipelines with Gemma: Retrieval and Augmented Generation (LangChain, FAISS)

Build advanced RAG pipelines integrating Gemma as the primary generator, implement vector stores with FAISS and hybrid embeddings, connect to enterprise knowledge bases via LangChain, practical tests on complex queries with grounding for increased reliability, optimization of latency for real-time applications, development of a complete RAG prototype on your capstone project, demonstration of up to 40% precision gains to boost professional efficiency.

Module 4Gemma AI Agents and Multimodal: Orchestration and Tools (AutoGen, LlamaIndex)

Develop autonomous agents based on Gemma using AutoGen and LlamaIndex frameworks for multi-step tasks, integration of vision and audio via multimodal extensions, exercises on enterprise scenarios such as document analysis or intelligent chatbots, error handling and reasoning loops, deployment of a collaborative agent swarm on real cases, ROI evaluation via automated workflow simulations, acquisition of skills to transform your business processes.

Module 5Gemma Deployment and Security: Secure Production (Docker, ONNX, Guardrails)

Prepare Gemma deployment in production with Docker containerization and ONNX export for fast inference, securing against jailbreaks and biases via Guardrails AI, monitoring with Prometheus and scaling on Kubernetes, exercises on AWS/GCP cloud infrastructures, full audit of your capstone project with load testing, professional documentation and maintenance plan, conclusion with certification of acquired skills for immediate enterprise implementation.