Generative AI and Responsible AI Practices with Google Cloud Course

The course offers the complete overview of how to build, deploy and maintain Generative AI solutions in the advanced AI and machine learning ecosystem of Google Cloud. The learners will learn major GenAI concepts, such as foundation models, Large Language Models (LLM), prompt engineering, data preparation, and model fine-tuning. Another key point made during the course is the need to adopt Responsible AI principles, including fairness, transparency, safety, and accountability, to make AI adoption in real-life settings ethical and secure.

Participants will gain hands-on experience with Google Cloud technologies such as Vertex AI, Model Garden, and Generative AI Studio to be able to create scalable AI applications that support the organizational objectives. Moreover, the course covers governance strategies, compliance issues, and optimal practices of monitoring AI models to minimize risks and maintain trust.

At the program conclusion, the learners will be prepared to create efficient GenAI workflows, combine the responsible AI models, and implement the industry-ready solutions to business operations. The course is one of the best that professionals can enroll in to update their skills since it is professionally conducted. SSDN Technologies is the provider of the program and it is famous as the Best Training Company, ensuring high-quality learning and practical expertise for every participant. 


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Learning Options for You

  • Live Training (Duration : 40 Hours)
  • Per Participant

Fee: On Request

Course Prerequisites

  • Basic understanding of AI/ML concepts
  • Familiarity with cloud computing fundamentals
  • Knowledge of Python (preferred but not mandatory)
  • Awareness of data security and privacy principles
  • Optional: Experience with Google Cloud services (Vertex AI, IAM)

Learning Objectives

This course provides a comprehensive introduction to building and deploying generative AI models using Google Cloud’s Vertex AI, foundation models, and responsible AI tools. Learners explore prompt engineering, model tuning, pipelines, and real-world use cases. The course emphasizes responsible AI design principles, including fairness, explainability, privacy, governance, and risk mitigation. Participants gain hands-on experience implementing enterprise-grade GenAI solutions while following Google Cloud’s recommended frameworks for safe, ethical, and compliant AI development.

Target Audience

  • AI/ML engineers exploring Google Cloud’s GenAI ecosystem
  • Data scientists and analysts working on enterprise AI projects
  • Cloud architects and developers adopting AI-driven applications
  • Tech leads responsible for AI governance and compliance
  • Students and professionals aiming to build AI responsibly
  • Organizations transitioning to safe and scalable AI adoption

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