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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 Google AI Studio: Mastering the Creation and Deployment of AI Models 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 Google AI Studio: Mastering the Creation and Deployment of AI Models 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 Google AI Studio: Mastering the Creation and Deployment of AI Models training is carried out through:
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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.
Presentation of Google AI Studio and Google Cloud AI services; account creation, interface overview, navigation, and project organization. Importing datasets, cleaning, exploration, and visualization in the studio. First practical steps: getting started with the collaborative environment and managing cloud resources.
Defining an AI project, selecting and importing pre-defined models or creating a custom model. Training setup, hyperparameter management, launching learning tasks. Analysis of results, interpretation of metrics, experimentation, and iteration to optimize performance. Use of integrated notebooks and leveraging generative AI (Vertex AI, Gemini models, etc.).
Preparation and deployment of a trained model via Google AI Studio on Google Cloud. Production deployment, API creation, and integration into a real application. Online performance tracking and monitoring, scalability management, security best practices, and model governance. Concrete case studies and exercises for complete AI cycle implementation.
Target audience
Developers, data scientists, project managers, and professionals wishing to leverage the capabilities of Google AI Studio for creating and deploying AI models.
Prerequisites
Basic knowledge of Python programming and notions of machine learning
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