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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 Training Vertex AI - Orchestrating Scalable AI Pipelines 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 Vertex AI - Orchestrating Scalable AI Pipelines 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 Vertex AI - Orchestrating Scalable AI Pipelines 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.
Dive into setting up a Vertex AI Workbench environment for reproducible experiments, create your first ML pipelines with custom Python components, integrate Kubeflow for hybrid orchestration, perform hands-on exercises on real enterprise datasets, test hyperparameter tuning automation, produce a functional deliverable pipeline with performance metrics and complete documentation for immediate production deployment.
Explore Vertex AI Studio to prototype generative models with Gemini and PaLM, perform fine-tuning on custom enterprise datasets, integrate vector embeddings for advanced RAG, conduct hands-on exercises on text and image generation, optimize prompt engineering for professional outputs, generate deliverables like a functional AI chatbot connected to your data, with quantitative performance evaluation and iterative adjustments for maximum accuracy.
Deploy your models on Vertex AI Endpoints for automatic scalability, configure real-time monitoring with custom alerts, implement secure CI/CD pipelines via Cloud Build, simulate critical enterprise cases with drift detection and explainability, perform exercises on cost management and GDPR compliance, produce a complete MLOps dashboard and rollback plan, ensuring professional resilience for your production AI applications.
Target audience
Data scientists, ML engineers, and cloud architects for professional skill development
Prerequisites
Advanced experience in Python, TensorFlow/PyTorch, Google Cloud Platform, and ML APIs
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