Cloud Certification
MULTI-CLOUD GENERATIVE AI PRACTITIONER
From Foundations to Agentic Builder: A 30-Hour Practitioner Curriculum across Google Cloud, AWS, and Microsoft Azure. Build functional agentic AI applications with hands-on labs & capstones.
Duration 30 Hours
Difficulty Intermediate
Rating 4.98 / 5.0
Enrolled 3,800
Course Overview
This practitioner-level curriculum takes learners with no prior programming experience from foundational Generative AI concepts to building and deploying functional, agentic AI applications across Google Cloud, AWS, and Microsoft Azure. Across 30 hours, learners compare the three major cloud AI ecosystems side by side, build hands-on labs in each, and complete capstone projects that combine multimodal AI, retrieval-augmented generation, agent frameworks, and production deployment.
What You Will Learn
Understand AI vs ML vs GenAI core concepts across Google Cloud, AWS, and Azure
Master industry leaders & advanced prompting techniques across Gemini, Claude & GPT-4
Build hands-on Retrieval-Augmented Generation (RAG) & Vector Database solutions
Develop Autonomous AI Agents using Google ADK and Model Context Protocol (MCP)
Master Vibe Coding, prompt engineering, and prompt-to-production workflows
Leverage AI Development Tools (Cursor, GitHub Copilot, Windsurf, Flowise & Langflow)
Process Multimodal AI (Vision & Speech) with Whisper, ElevenLabs, and multimodal LLMs
Deploy enterprise AI workloads on GCP Vertex AI, AWS Bedrock & Azure OpenAI
Containerize & host Local LLMs using Ollama & Docker microservices
Complete end-to-end Capstone Projects combining AI agents, RAG, and multi-cloud deployment
Step-by-Step Curriculum
Course Learning Roadmap
Course Syllabus & Modules
Core AI/ML/GenAI/Agentic AI concepts, terminology & evolution
Training vs Inference, Supervised vs Unsupervised learning foundations
Overview of Google Cloud Vertex AI, AWS Bedrock & Azure OpenAI Service
Prerequisites
- Python basics: variables, functions, running a notebook
- Basic AI/ML concepts: what a model is, training vs. inference
- Suggested primer: Microsoft Learn – Fundamentals of AI, or Google Cloud Skills Boost – Introduction to Generative AI
Target Audience
- Aspiring AI Practitioners & Developers
- Technical Product Owners & Solutions Architects
- Career Switchers seeking practical cross-cloud GenAI fluency
- Cloud & DevOps Engineers
Limited Seats for Upcoming BatchAdmissions Open 2026
Red Hat Exam Voucher Support
24/7 Remote Lab Access Included
Guaranteed 100% Placement Assistance