Detailed Course Syllabus
Module 1: Cloud & Generative AI Foundations
Phase 1- ✓Introduction to Google Cloud Console, Cloud IAM, and Cloud Storage basics
- ✓Understanding GenAI concepts, Transformer models, and LLM architectures
- ✓The Google Gemini Model Family (Gemini Pro, Flash, Ultra) and API usage
- ✓Prompt engineering techniques, system instructions, and temperature tuning
Module 2: Building with Vertex AI
Phase 2- ✓Vertex AI Studio - Interactive testing of chat, text, and multimodal prompts
- ✓Vertex AI Search and Conversation - Rapid creation of enterprise-ready search applications
- ✓Building Retrieval-Augmented Generation (RAG) pipelines for document processing
- ✓Embedding creation using Vertex AI Text Embeddings and custom vector indexing
Module 3: Advanced AI Agents & Orchestration
Phase 3- ✓LLM Orchestration frameworks: Connecting Gemini API with LangChain and LlamaIndex
- ✓Building Agentic workflows with tool calling, function calling, and API integration
- ✓AI Agent grounding using Google Search and database connectors
- ✓Session management and chat history storage using Cloud Firestore
Module 4: Enterprise AI MLOps & Monitoring
Phase 4- ✓Deploying custom AI APIs and backends on Google Cloud Run (Serverless Containerization)
- ✓Monitoring LLM application performance, safety parameters, and costs on GCP
- ✓A/B testing different prompts and model versions using Cloud Logging and Vertex AI
- ✓Graduation Project: Build and deploy an enterprise-grade AI chatbot on Google Cloud
Download Official Syllabus
Get a comprehensive offline PDF of this syllabus containing all lesson outcomes, lab assignments, and prerequisites.
Download CurriculumCourse Key Highlights
- Build with Google Gemini 1.5 Pro
- Vertex AI Studio & Model Builder
- RAG & Agentic Workflows
- Production AI App Deployments
- 100% Practical Hands-on Sandbox Labs
- Mock Technical Interviews & Resume Auditing
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