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Course Outline
Introduction
- The Generative AI Leader certification: value proposition and target audience.
- Exam format, domains, weightings, and preparation strategies.
Fundamentals of Gen AI (~30%)
- Core gen AI concepts and use cases (AI, ML, LLMs, foundation models, multimodal and diffusion models, prompt engineering).
- Machine learning approaches (supervised, unsupervised, reinforcement) and the machine learning lifecycle.
- Criteria for selecting foundation models (modality, context window, cost, performance, customization).
- Data types and data quality in gen AI (structured vs. unstructured, labeled vs. unlabeled).
- The gen AI landscape layers and Google’s foundation models (Gemini, Gemma, Imagen, Veo).
Google Cloud's Gen AI Offerings (~35%)
- Google Cloud’s gen AI strengths and AI-optimized infrastructure (TPUs, GPUs, hypercomputer).
- Prebuilt offerings: Gemini App and Gemini Advanced, Gemini for Google Workspace, Gemini Enterprise.
- Customer experience solutions: Customer Engagement Suite (Conversational Agents, Agent Assist, Conversational Insights).
- Developer enablement: Vertex AI / Agent Platform, Model Garden, and RAG offerings.
- Gen AI agent tooling (extensions, functions, data stores) and relevant Google Cloud services.
Techniques to Improve Gen AI Model Output (~20%)
- Addressing foundation model limitations (knowledge cutoff, bias, hallucinations, edge cases).
- Prompt engineering techniques (zero-shot, one-shot, few-shot, role-based, prompt chaining, chain-of-thought, ReAct).
- Grounding and Retrieval-Augmented Generation (RAG).
- Sampling parameters for controlling output (temperature, top-p, token count, safety settings).
Business Strategies for Successful Gen AI Solutions (~15%)
- Implementation steps and solution selection methodology.
- Secure AI principles and Google’s Secure AI Framework (SAIF).
- Responsible AI considerations: privacy, bias and fairness, accountability, and explainability.
Exam Preparation
- Sample questions and domain-by-domain review.
- Full mock exam with answer analysis.
- Study plan and exam-day strategy.
Summary and Next Steps
Requirements
Prerequisites
- No technical prerequisites are required.
- A general familiarity with business technology is beneficial.
Audience
- Leaders, managers, and decision-makers.
- Business professionals in any role who are adopting generative AI.
- Individuals preparing for the Google Cloud Generative AI Leader certification.
14 Hours
Testimonials (1)
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