TRAINING List
Developing APIs with Google Cloud's Apigee API platform (T-APIENG-B)
In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API life cycle, and how the Apigee API platform helps you manage all aspects of the life cycle. You learn how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform.
Managing Google Cloud's Apigee API Platform for Hybrid Cloud (T-APIHYB-B)
Learn how to install and manage Google Cloud's Apigee API Platform in a hybrid cloud. This course uses lectures, hands-on labs, and supplemental resources to show you how to design, install, manage, and scale your Apigee API Platform.
Customer Experiences with Contact Center AI - Dialogflow ES (CCAIDES)
Welcome to "Customer Experiences with Contact Center AI" with a focus on Dialogflow ES. In this course, learn how to design, develop, and deploy customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, virtual agent development utilizes Dialogflow ES. You'll also learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale.
Customer Experiences with Contact Center AI - Dialogflow CX (CCAIDCX)
Welcome to "Customer Experiences with Contact Center AI" with a focus on Dialogflow CX. In this course, learn how to design, develop, and deploy customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, virtual agent development utilizes Dialogflow CX. You'll also learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale.
Deploying and Managing Windows Workloads on Google Cloud (DMWWGC)
This course teaches you about deploying and managing Microsoft Windows® workloads on Google Cloud. This course uses lectures and hands-on labs to show you how to plan and configure Microsoft Windows Server and Microsoft SQL Server in Google Cloud. You will configure identity solutions including Managed Service for Microsoft Active Directory, deploy Windows workloads to Compute Engine and Google Kubernetes Engine, and learn to manage and operate Windows workloads with Cloud Console, Cloud Logging, and Cloud Monitoring.
Google Cloud Platform Fundamentals for AWS Professionals (GCP-FAP)
Este curso de 6 horas con labs presenta a los profesionales de AWS las funciones principales de Google Cloud Platform (GCP) en los cuatro pilares de la tecnología: herramientas de redes, procesamiento, almacenamiento y base de datos. Este curso está diseñado para los arquitectos de soluciones de AWS y administradores de SysOps familiarizados con las funciones y la configuración de AWS que desean obtener experiencia en la configuración de productos de GCP de forma inmediata. Los participantes obtienen rápidamente detalles de las diferencias, las similitudes y los procedimientos iniciales con presentaciones, demostraciones y labs prácticos.
Google Cloud Fundamentals for Azure Professionals (GCPAZURE)
This course teaches Azure professionals about the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, solutions architects, and SysOps administrators who are familiar with Azure features and setup and want to gain experience configuring Google Cloud products immediately. This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud.
Application Development with Cloud Run (ADCR)
This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, implement, deploy, secure, manage, and scale new (greenfield) and existing (brownfield) applications on Google Cloud using Cloud Run.
Analyzing and Visualizing Data with Looker (AVDL)
This course is an introductory-level training that outlines Looker’s capabilities for working with data and provides guided demos and hands-on practice with Looker functionality for data exploration, analysis and visualization.
This course enables learners to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Participants will learn how to leverage Looker's modern analytics platform to find and explore relevant content in their organization’s Looker instance, ask questions of data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
Architecting Hybrid Cloud Infrastructure with Anthos (T-AHYBRID-I)
This four day, instructor-led course prepares students to modernize, manage, and observe their containerized applications using Kubernetes, in Google Cloud, AWS, Azure, and on-premises. Through presentations and hands-on labs, participants explore Google Kubernetes Engine (GKE), Connect Agent, Anthos Service Mesh and Anthos Config Management features. Participants learn how to work with containerized applications even when split between multiple clusters, hosted by multiple cloud providers or on-premises. This course is a continuation of Architecting with GKE and assumes direct experience with the technologies covered in that course.
Data Integration with Cloud Data Fusion (DICDF)
This 2-day course introduces learners to Google Cloud’s data integration capability using Cloud Data Fusion. In this course, we discuss challenges with data integration and the need for a data integration platform (middleware). We then discuss how Cloud Data Fusion can help to effectively integrate data from a variety of sources and formats and generate insights. We take a look at Cloud Data Fusion’s main components and how they work, how to process batch data and real time streaming data with visual pipeline design, rich tracking of metadata and data lineage, and how to deploy data pipelines on various execution engines.
Advanced Machine Learning with TensorFlow on Google Cloud Platform (MLTF)
What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets?
Machine Learning on Google Cloud (MLGC)
What is machine learning, and what kinds of problems can it solve? Why are neural networks so popular right now? How can you improve data quality and perform exploratory data analysis? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent? In this course, you'll learn how to write distributed machine learning models that scale in Tensorflow 2.x, perform feature engineering in BQML and Keras, evaluate loss curves and perform hyperparameter tuning, and train models at scale with Cloud AI Platform.
From Data to Insights with Google Cloud Platform (DIGCP)
Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course!
This two-day instructor-led class teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course covers data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization.
Preparing for the Professional Data Engineer Examination (PPDEE)
This full-day instructor-led course helps prospective candidates structure their preparation for the Professional Data Engineer exam. The session covers the structure and format of the examination and its relationship to other Google Cloud certifications. Through lectures, quizzes, and discussions, candidates will familiarize themselves with the domain covered by the examination in order to devise a preparation strategy. Rehearses useful skills including exam question reasoning and case comprehension. Tips. Review of topics from the Data Engineering curriculum.
Serverless Data Processing with Dataflow (SDPF)
This training is intended for big data practitioners who want to further their understanding of Dataflow in order to advance their data processing applications. Beginning with foundations, this training explains how Apache Beam and Dataflow work together to meet your data processing needs without the risk of vendor lock-in.The section on developing pipelines covers how you convert your business logic into data processing applications that can run on Dataflow. This training culminates with a focus on operations, which reviews the most important lessons for operating a data application on Dataflow, including monitoring, troubleshooting, testing, and reliability.
Data Engineering on Google Cloud Platform (DEGCP)
This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data.
Analyzing and Visualizing Data with Looker (AVDL)
This course is an introductory-level training that outlines Looker’s capabilities for working with data and provides guided demos and hands-on practice with Looker functionality for data exploration, analysis and visualization.
This course enables learners to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Participants will learn how to leverage Looker's modern analytics platform to find and explore relevant content in their organization’s Looker instance, ask questions of data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
Developing Data Models with LookML (DDMLML)
This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
From Data to Insights with Google Cloud Platform (DIGCP)
Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course!
This two-day instructor-led class teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course covers data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization.
Getting Started with Google Kubernetes Engine (GCP-GSGKE)
Learn to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. You also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.
Developing Applications with Google Cloud Platform (DAGCP)
In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
Logging, Monitoring, and Observability in Google Cloud (LMOGC)
This three-day instructor-led course teaches participants techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud. Guided by the principles of Site Reliability Engineering (SRE), and using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.
Networking in Google Cloud Platform (NGCP)
This 2-day instructor-led course gives participants a broad study of networking options on Google Cloud Platform. Through presentations, demonstrations, and hands-on labs, learners explore and deploy GCP networking technologies, such as Google Virtual Private Cloud (VPC) networks, subnets, firewalls, interconnection among networks, load balancing, Cloud DNS, and Cloud CDN. The course also covers common network design patterns and automated deployment using Cloud Deployment Manager.
Architecting with Google Kubernetes Engine (AGKE)
This class is intended for the following participants:
Cloud architects, administrators, and SysOps/DevOps personnel
Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform.
Architecting with Google Cloud Platform: Design and Process (AGCP-DP)
This two-day instructor-led training class equips students to build highly reliable and efficient solutions on Google Cloud Platform, using proven design patterns and the principles of Google Site Reliability Engineering (SRE). It is a continuation of the Architecting with Google Cloud Platform: Infrastructure course and assumes hands-on experience with the technologies covered in that course.
Through a combination of presentations, demos, and hands-on labs, participants learn to design GCP deployments that are highly reliable and secure; and how to operate GCP deployments in a highly available and cost-effective manner.
Google Cloud Fundamentals: Big Data and Machine Learning (GCF-BDM)
This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
Preparing for the Associate Cloud Engineer Examination (PPACE)
This course uses lectures, demos, and hands-on labs to help you prepare for Google Cloud's Associate Cloud Engineer certification exam. You'll learn about the structure, format, and domain of the exam so that you can create your study plan, along with how this certification relates to other Google Cloud certifications.
Getting Started with Google Kubernetes Engine (GCP-GSGKE)
Learn to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. You also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.
Cloud Digital Leader (CDL)
If you’re wondering how cloud can transform your business then this course is for you. Aimed at business leaders new to cloud, this course provides insight into Google's approach to digital transformation, and how to embrace cloud in your business.
This training is designed to give you foundational knowledge about cloud technology, data, and Google Cloud products that enable digital transformation. Empowering you and your team(s) to contribute to cloud-related business initiatives in your organization.
Google Cloud Fundamentals: Core Infrastructure (GCF-CI)
This one-day instructor-led class provides an overview of Google Cloud Platform products and services. Through a combination of presentations, demos, and hands-on labs, participants learn the value of Google Cloud Platform and how to incorporate cloud-based solutions into business strategies.
Architecting with Google Compute Engine (AGCE)
This three-day instructor-led class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.