Deploy and Manage Generative AI Models on Google Cloud Course

In the course Deploy and Manage Generative AI Models on Google Cloud, the learners are supposed to be equipped with the practical skills that they need to develop, deploy, monitor and optimize the generative AI solutions in the context of the advanced AI and ML ecosystem of Google cloud. In this course, I have gained a solid understanding of the concepts of generative AI, large language models (LLMs), and Google Cloud platforms, including Vertex AI, Model Garden, and AI Studio. Learners will get practical rise in implementation of pre-trained models, fine-tuning them in certain business scenarios, and incorporating generative AI into practice.

The course emphasizes best practices of model lifecycle management such as versioning, scalability, optimization of performance, security, and cost control. The participants will also be taught to deal with prompts, appraise models output, consider responsible AI and oversee the deployed models to ensure reliability and compliance. Practical labs and the real-life situations will help learners get to know how to optimize the generative AI workloads on Google Cloud.

The last stage of the course is focuses on enterprise-level deployment strategies, automation, and governance enabling the professionals to operate the generative AI solutions with full confidence in the production environment. This course is provided through SSDN Technologies, a Best Training Company, and it offers industry-aligned training and expert advice to enable the learners to remain abreast of the fast-changing world of AI. 
 


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Learning Options for You

  • Live Training (Duration : 24 Hours)
  • Per Participant

Fee: On Request

Course Prerequisites

  • Basic understanding of machine learning concepts
  • Familiarity with Python and APIs
  • Knowledge of Google Cloud fundamentals
  • Introductory experience with AI or ML models is beneficial

Learning Objectives

This course teaches learners how to deploy, manage, and scale generative AI models on Google Cloud. Participants gain hands-on experience with Vertex AI, model endpoints, prompt engineering, security, monitoring, and cost optimization. The course emphasizes production-ready deployments, responsible AI practices, and real-world enterprise use cases.

Target Audience

  • Machine learning and AI engineers
  • Data scientists and AI practitioners
  • Cloud and platform engineers
  • DevOps engineers supporting ML workloads
  • IT professionals adopting generative AI solutions

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