[NEW] The Ultimate Generative AI Leader Cert. Training

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[Latest Syllabus] Pass The Generative AI Leader Exam On Your First Attempt | 2 Full Practice Exams & 160+ Quiz Questions

What you'll learn

  • Comprehensive Preparation For The Google Cloud Generative AI Leader Exam: 8h High-Quality Video Content + A Total Of 263 Questions & Explanations.
  • [Up-To-Date - 2025 Exam Syllabus] Master The Generative AI Leader Exam - No Previous Knowledge Needed.
  • [Downloadable] Recap Of Key Concepts - PDF file (75 Pages).
  • Differentiate between Artificial Intelligence, Machine Learning, and Deep Learning.
  • Identify different data types used in Machine Learning and evaluate data quality requirements for successful projects
  • Explore the applications of Computer Vision and Natural Language Processing (NLP).
  • Learn the key steps involved in the Machine Learning process.
  • Distinguish and apply the main types of Machine Learning: Supervised, Unsupervised, Reinforcement, and Semi-Supervised Learning.
  • Map out the entire Machine Learning lifecycle including development, deployment, and maintenance phases
  • Assess data accessibility and quality issues that can impact Machine Learning project success
  • Explain how machine learning algorithms transform raw data into intelligent predictions and decisions
  • Map the current generative AI landscape and position Google's foundation models within the competitive ecosystem
  • Evaluate Gemini's multimodal capabilities for text, code, and reasoning tasks across different business applications
  • Compare Gemma's lightweight architecture with larger models and determine when efficiency trumps raw power
  • Analyze Imagen's text-to-image generation capabilities and assess its potential for creative and commercial projects
  • Select the most appropriate Google foundation model based on specific project requirements and constraints
  • Analyze Google's AI-first strategy and explain how it creates competitive advantages in the cloud computing market
  • Evaluate Google Cloud's enterprise-ready AI features including security, privacy, reliability, and scalability measures
  • Examine Google Cloud's Hypercomputer architecture, TPUs, and GPUs to understand their role in powering generative AI workloads
  • Determine the key factors that make Google Cloud suitable for scaling enterprise AI initiatives
  • Navigate Gemini App subscription tiers and select the right plan for personal or business needs
  • Understand Vertex AI Search and Google Search solutions in business applications
  • Discover Google Agentspace capabilities and recognize its applications across different industries
  • Explore how Gemini AI enhances Gmail, Docs, and Sheets for improved productivity
  • Understand conversational agents and customer service tools that improve engagement
  • Identify which prebuilt Google AI solutions best fit specific workflow challenges
  • Learn about RAG and grounding techniques that improve AI response accuracy and contextual relevance
  • Understand Vertex AI Platform's unified approach to the complete AI development lifecycle from training to deployment
  • Understand Vertex AI Agent Builder's capabilities for creating autonomous AI agents that handle multi-step tasks
  • Discover how Google Cloud services and APIs provide foundational tools for building sophisticated agent systems
  • Learn how AI agents interact with external environments through extensions, functions, and data stores to perform real-world actions
  • Understand Google Cloud's solutions like grounding, RAG, and prompt engineering for building more reliable AI systems
  • Identify common foundation model limitations including hallucinations, bias, and knowledge cutoffs that impact AI performance
  • Learn how continuous monitoring and evaluation using Vertex AI ensures robust, production-ready AI applications
  • Understand the fundamental principles of prompt engineering that combine creativity with systematic approaches for optimal LLM performance
  • Learn essential prompting techniques including zero-shot, few-shot, and role-based prompting for different use cases
  • Discover advanced strategies like chain-of-thought reasoning and inference parameters that control AI model behavior and output quality
  • Identify different types of generative AI business solutions and understand how they address real-world organizational challenges
  • Learn the essential steps and considerations for systematically integrating generative AI into organizational workflows
  • Understand key decision factors including business requirements, technical constraints, and ROI measurement for successful AI implementation
  • Understand why security must be integrated throughout every stage of the machine learning lifecycle from development to deployment
  • Learn Google's Secure AI Framework (SAIF) and how it addresses unique security challenges in generative AI systems
  • Discover Google Cloud security tools including IAM, Security Command Center, and monitoring services for comprehensive AI protection
  • Understand why responsible AI practices including transparency and ethics are essential for sustainable business success and stakeholder trust
  • Learn about privacy considerations in generative AI and discover protective measures like data anonymization and pseudonymization techniques
  • Discover how data quality impacts bias and fairness, and understand strategies for building accountable and explainable AI systems

This course includes:

  • 8 hours on-demand video
  • 2 practice tests
  • 5 articles
  • 7 downloadable resources
  • Access on mobile and TV
  • Full lifetime access
  • Certificate of completion

Requirements

  • No previous Artificial Intelligence or Cloud Computing knowledge or experience needed

Course link - https://bitli.in/t7EeaP9  


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