1. Course Syllabus

   Module 1: Introduction to Generative AI and Google Cloud Platform (4 Hours)

   • Overview of Generative AI
   • Introduction to Google Cloud Platform
   • Generative AI use cases
   • Setting up GCP environment

   Module 2: Fundamentals of Machine Learning and Deep Learning on GCP (4 Hours)

   • Basics of machine learning
   • Deep learning fundamentals
   • TensorFlow and Keras overview
   • Google AI and ML services

   Module 3: Vertex AI Platform (4 Hours)

   • Overview of Vertex AI
   • Creating datasets and training models
   • AutoML and custom training workflows
   • Model monitoring and management

   Module 4: Foundation Models and Large Language Models (LLMs) (5 Hours)

   • Introduction to Foundation Models
   • Understanding LLMs and their capabilities
   • Google's Generative AI models: PaLM, Gemini
   • Practical hands-on session with LLMs

   Module 5: Generative AI Applications and Use Cases (5 Hours)

   • Text generation, summarization, and translation
   • Image and video generation
   • Generative AI in business applications
   • Hands-on labs with real-world scenarios

   Module 6: Responsible and Ethical AI (4 Hours)

   • Understanding AI ethics and responsible AI
   • Bias, fairness, and explainability in Generative AI
   • Compliance and privacy in Generative AI
   • Best practices and guidelines

   Module 7: Deployment and Scaling Generative AI Models (5 Hours)

   • Deployment strategies on Google Cloud
   • Managing Generative AI pipelines
   • Using containers and Kubernetes on GKE
   • Optimizing performance and cost management

   Module 8: Integration of Generative AI into Business Solutions (5 Hours)

   • Creating business-specific Generative AI solutions
   • Case studies across industries
   • Integration with existing IT ecosystems
   • Project session: Building a Generative AI business prototype

   Module 9: Preparing for Google Cloud Certification (4 Hours)

   • Review of key concepts
   • Exam tips and preparation strategies
   • Mock exams and review sessions

    

Key Features

• Hands-on Labs: Extensive practical sessions using Vertex AI, TensorFlow, and other Google Cloud services.
• Certification Alignment: Content aligned with Google Cloud certification paths to prepare attendees for official exams.
• Real-world Use Cases: Integration of industry scenarios across healthcare, finance, retail, and more.
• Ethical AI Considerations: Emphasis on responsible AI practices, fairness, and bias management.
• Expert Instructors: Guidance from professionals certified in Google Cloud and Generative AI.
• Comprehensive Learning Materials: Access to detailed documentation, lab guides, and practice exercises.
• Interactive Learning: Engaging sessions with quizzes, project-based assessments, and collaborative exercises.