Customer Engagement Suite with Google AI Architecture
Earned Jul 3, 2024 EDT
Earn the Introductory skill badge by completing the Cloud Speech API: 3 Ways course, where you learn how to use speech related API tools to synthesise and transcribe speech.
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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.
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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.
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Complete the introductory Create and Manage AlloyDB Instances skill badge to demonstrate skills in the following: performing core AlloyDB operations and tasks, migrating to AlloyDB from PostgreSQL, administering an AlloyDB database, and accelerating analytical queries using the AlloyDB Columnar Engine.
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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.
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Complete the introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.
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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.
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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.
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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API and Video Intelligence. Want extra help? 1-minute videos walk you through key concepts for each lab.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.
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Configure and Maintain CCAIP as an Admin is a course that provides end users with essential learning about the core features, functionality, reporting, and configuration information most relevant to the role. This course is most appropriate for those who perform administrative functions to support the operation of the contact center as well as analyze, troubleshoot, and configure the platform to best meet the demands of customers. While this program will review some monitoring and reporting aspects, those topics are explored in depth in the course titled, “Managing Functions and Reporting with CCAIP.”
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Manage Functions and Reporting with CCAI Platform provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCAI Platform.
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This course teaches contact center agents about the core agent features and functionality in Contact Center as a Service (CCaaS). CCaaS is a unified contact center platform that accelerates an organization's ability to leverage and deploy contact centers without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.
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Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
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This course explores the foundational principles of conversation design to craft engaging and effective chatbot experiences that emulate human-like experiences.
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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
Cloud Speech API: 3 Ways
Earned Feb 9, 2025 EST
Build Real World AI Applications with Gemini and Imagen
Earned Feb 4, 2025 EST
Prompt Design in Vertex AI
Earned Feb 3, 2025 EST
Introduction to Data Engineering on Google Cloud
Earned Dec 22, 2024 EST
Gemini for Application Developers
Earned Sep 14, 2024 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned Sep 8, 2024 EDT
Create and Manage AlloyDB Instances
Earned Sep 1, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned Aug 31, 2024 EDT
Manage Kubernetes in Google Cloud
Earned Aug 31, 2024 EDT
Monitor and Manage Google Cloud Resources
Earned Aug 31, 2024 EDT
Build Infrastructure with Terraform on Google Cloud
Earned Aug 31, 2024 EDT
Security Best Practices in Google Cloud
Earned Aug 31, 2024 EDT
Mitigating Security Vulnerabilities on Google Cloud
Earned Aug 30, 2024 EDT
Baseline: Data, ML, AI
Earned Aug 30, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Aug 30, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned Aug 27, 2024 EDT
Google Cloud Fundamentals for AWS Professionals
Earned Aug 27, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Aug 27, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned Aug 26, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned Aug 26, 2024 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned Aug 25, 2024 EDT
Preparing for your Professional Data Engineer Journey
Earned Aug 25, 2024 EDT
Generative AI Explorer - Vertex AI
Earned Aug 22, 2024 EDT
Configure and Maintain CCAIP as an Admin
Earned Jul 18, 2024 EDT
Manage Functions and Reporting with CCAIP
Earned Jul 17, 2024 EDT
Handle Consumer Interactions with CCaaS
Earned Jul 16, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned Jul 16, 2024 EDT
Conversation Design Fundamentals
Earned Jul 16, 2024 EDT
Customer Engagement Suite with Google AI Architecture
Earned Jul 3, 2024 EDT