Course Overview:

This one-day instructor-led course is designed for technical professionals and solution architects who are ready to take their generative AI ideas into production. The course guides learners through every critical stage of deploying generative AI: from experimentation and unit testing, to productionizing pipelines, safeguarding applications, and monitoring performance. Participants engage with Vertex AI tools, including pipelines, Gemini APIs, and evaluation playbooks, through interactive lectures and hands-on labs. 

After completing this course, participants will be able to:

  • Understand production-level challenges in deploying generative AI systems
  • Manage experimentation with unit testing and rapid iteration
  • Create robust pipelines for generative AI using Vertex AI
  • Apply safeguards using Gemini APIs and monitoring tools
  • Monitor, log, and evaluate deployed LLMs
  • Use the Vertex AI Evaluations Playbook for real-world model assessments

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Key Features:

  • Full-Day Training: Structured into modules with labs, breaks, and a final wrap-up 

  • Vertex AI Hands-On Labs: Includes pipeline setup, Gemini API safeguarding, and model evaluations 

  • Real-World Focus: Learn to move from idea to secure, scalable production workflows 

  • Evaluation-Ready: Use the Gemini Evaluation Playbook to assess performance and safety

  • End-to-End View: From experimentation to deployment and monitoring in production

Prerequisites:

  • A working knowledge of generative AI fundamentals, Google Cloud infrastructure, and some experience with Vertex AI is recommended for successful participation in this course.

    • Why choose CloudThat as your training partner?

    • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP.
    • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios.
    • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set.
    • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills.
    • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course.
    • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals.
    • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge.
    • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training.

    Learning Objective:

    • After completing this course, students will be capable of designing and deploying generative AI solutions in production with proper experimentation, safeguarding, and monitoring using Vertex AI tools and practices.

    Course Outline: Download Course Outline

    Topics

    • Core concepts in production-scale generative AI
    • Challenges of GenAI at scale
    • Overview of GenAI lifecycle

    Objectives

    • Understand requirements for deploying GenAI in production
    • Describe typical lifecycle and constraints for GenAI systems

    Activities

    • Lecture, Demo, Discussion

    Topics

    • Experimentation strategies
    • Versioning and evaluation
    • Designing prompt tests

    Objectives

    • Apply experimentation principles to GenAI pipelines
    • Design unit tests for prompts and models

    Activities

    • Lecture, Lab 1: Unit Testing Generative AI Applications

    Topics

    • Serving pipelines and model deployment
    • Safety and reliability in production GenAI
    • Evaluation loops and feedback

    Objectives

    • Understand methods for deploying GenAI application
    • Build safe and scalable GenAI pipelines

    Activities

    • Lecture, Lab 2: Vertex Pipelines OR Safeguarding with Vertex AI Gemini API

    Topics

    • Observability for LLMs
    • Logging strategies and error analysis
    • Model monitoring and performance evaluation

    Objectives

    • Implement effective logging and monitoring for LLM systems
    • Analyze logs and evaluations to improve GenAI applications

    Activities

    • Lecture, Lab 3: Vertex AI Gemini Evaluations Playbook

    Topics

    • Review of key concepts
    • Q&A session
    • Course feedback and next steps

    Objectives

    • Consolidate learnings from the course
    • Clarify open questions and review lab takeaways

    Activities

    • Wrap-up, Q&A, Discussion

    Certification Details:

      CloudThat Course Completion Certificate

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    Course ID: 26135

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    FAQs:

    The course focuses on deploying generative AI applications in production environments using Google Cloud’s Vertex AI.

    This is a full-day, instructor-led course with structured lectures, labs, breaks, and discussions.

    Labs include unit testing GenAI apps, creating pipelines with Vertex AI, applying safeguards with Gemini APIs, and evaluating models using the Gemini Playbook.

    Modules include introduction, managing experimentation, productionizing GenAI, logging and monitoring, and wrap-up.

    Yes, including pipelines, Gemini API, and evaluation workflows.

    Yes, the course includes labs specifically focused on safeguarding using Gemini APIs.

    Absolutely. A full module addresses logging, observability, and monitoring LLMs in production.

    Familiarity with Google Cloud, basic GenAI concepts, and hands-on experience with Vertex AI will help you succeed.

    Yes. Labs span 3+ hours with real tools and workflows in the Google Cloud ecosystem.

    Yes. You will receive a CloudThat course completion certificate.

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