This GCP-AMLTF: Advanced Machine Learning with TensorFlow on Google Cloud course will give you hands-on experience optimizing, deploying, and scaling a variety of production ML models. You’ll learn how to build recommendation systems
and scalable, accurate, and production-ready models for structured data, image data, time series, and natural language text.
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The most automated and scalable managed Kubernetes platform.
- Learn how to create and deploy containerized applications on Google Kubernetes Engine (GKE).
- This GCP-GSGKE: Getting Started with Google Kubernetes Engine course features a combination of lectures, demos, and hands-on labs to help you explore and deploy solution elements including infrastructure components like pods, and containers.
Limited Time Offer: Get up to 45% OFF selected Google Cloud courses in H2 2025 via our Google Cloud Certified program.
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In this course, you’ll learn the fundamentals and best practices of SRE, the importance of adopting an SRE culture, and how SRE can improve collaboration between IT and business leaders—and help the entire organization succeed.
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The Logging, Monitoring and Observability in Google Cloud training course teaches participants techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud.
Learn how to monitor, troubleshoot, and improve your infrastructure and application performance. Guided by the principles of Site Reliability Engineering (SRE), this official Google Cloud course features a combination of lectures, demos, hands-on labs, and real-world case studies. In this course, you’ll gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, and profiling CPU and memory usage.
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This GCP-MLOF: MLOps (Machine Learning Operations) Fundamentals course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.
Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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In this GCP-MPGC: ML Pipelines on Google Cloud course, you will learn about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. The first few modules discuss pipeline components, pipeline orchestration with TFX, how you can automate your pipeline through CI/CD, and how to manage ML metadata.
Then we will discuss how to automate and reuse ML pipelines across multiple ML frameworks such as tensorflow, pytorch, scikit learn, and xgboost. You will also learn how to use Cloud Composer to orchestrate your continuous training pipelines, and MLflow for managing the complete machine learning life cycle.
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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.
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If you are new to Google Workspace, this training will equip you with the skills you need to be productive in the workplace. Through a series of lectures, demonstrations, and hands-on activities, you will become proficient in the use of the following core Google Workspace applications: Gmail, Google Calendar, Google Drive, Google Docs, Google Sheets, Google Slides, Google Meet and Google Chat.
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This GCP-AWS: Google Cloud Fundamentals for AWS Professionals course is designed for AWS system administrators, solutions architects, and SysOps administrators who are familiar with AWS 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.
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This course broadens the skills of the student who are required to implement and manage a Kubernetes-based Platform as a Service (PaaS) environment based on Red Hat OpenShift Container Platform on Power Systems. The course covers basic administration and configuration of Red Hat OpenShift Container Platform within a POWER processor-based server configured with IBM PowerVC. Hands-on exercises reinforce the lecture material, and allow students to use the Red Hat OpenShift Container Platform to work with images, applications, and manage a cluster.
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This course covers the steps to follow to update a Red Hat OpenShift Container Platform 4.3.18 environment on Power Systems to 4.3.23. Lessons learned, and hints and tips will be provided to help you perform the update successfully.
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This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables.
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This course teaches IBM Spectrum LSF 10.1 version.
The course is designed to give system administrators the knowledge required to implement and maintain LSF in their working environment. They will gain a solid understanding of workload resource management, cluster configuration and administration. The workshops provide valuable experience with the installation of LSF, cluster configuration and administration. The system administrator will also learn helpful hints and tips and develop fundamental troubleshooting skills.
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This course is designed to introduce students to IBM Data Science Experience. The course covers how to create and set up a project and to be familiar with how to create, code, collaborate, and share notebooks while working with a variety of data sources to analyze data.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
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This course teaches developers, database administrators, and system programmers various features of SQL, including column functions, grouping, unions, subqueries, and maintaining data.
Note: Guided eLearning is a self-paced offering which includes web-based content for self-study and videos (including audio) that demonstrate activities.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
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This offering teaches cloud database support staff how to manage access of users and privileges to a dashDB for Analytics or dashDB for Transactions database.
Note: Guided eLearning is a self-paced offering which includes web-based content for self study and videos (including audio) that demonstrate the hands-on activity.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. http://www.ibm.com/training/terms
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This course is intended for Developers, Database Administrators, and System Programmers who require further insight into the SQL language.
Note: Guided eLearning is a self-paced offering which includes web-based content for self-study and videos (including audio) that demonstrate activities.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
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In this course, you learn how to define automation policy for IBM System Automation for z/OS® (SA z/OS).
You learn how to create policy definitions for systems, applications, application groups, and monitor resources. This is delivered in an environment with multiple opportunities for hands-on lab exercises. You define automation policy for several environments: single system and multiple system within a basic sysplex. The System Automation for z/OS automation manager and automation agent run in a z/OS 2.2 environment. The automation platform, Tivoli® NetView for z/OS is at version 6 release 2. -
IBM FlashSystem 9100 system is an all-flash, powerful end-to-end Non-Volatile Memory Express (NVMe) enterprise storage solution that combines the performance of IBM FlashCore technology.
FlashSystem 9100 is built on the efficiency of IBM Spectrum Virtualize, and delivered on a proven IBM software solution with extremely low latencies for your multi cloud deployments.This course introduces the FlashSystem 9100 NVMe Control Enclosure models: IBM 9846/9848 FlashSystem 9110, Model AF7 and IBM 9846/9848 FlashSystem 9150, Model AF8.
It also focuses on the integration of FlashSystem 9100 SAS-Attached expansion enclosures; scalability performance with NVMe; and the intuitive sight of IBM Storage Insights which helps optimize the storage infrastructure using predictive analytics.If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. http://www.ibm.com/training/terms
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IBM UrbanCode Deploy is a tool for standardizing and simplifying the process of deploying software components to each environment in your development cycle. When you use blueprints for OpenStack-based clouds, you can use a full-stack approach to simultaneously model the application and infrastructure layers of your deployment.
In this course, you learn how to administer the cloud through both the Blueprint Designer and the Horizon user interface. Hands-on labs use IBM UrbanCode Deploy in a cloud environment and cover integrations with an OpenStack back-end and IBM UrbanCode Deploy, modeling the cloud infrastructure and application layers, provisioning environments from blueprints, creating and using configuration files, updating a running environment, and using Git repositories to store and manage blueprints.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
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IBM PowerVC for Private Cloud, an infrastructure-as-a-service (IaaS) offering, provides a self-service cloud portal for IBM Power Systems and is built on OpenStack. OpenStack is a collection of open source software projects that enterprises or service providers can use to setup and run their cloud compute and storage infrastructure. IBM PowerVC for Private Cloud provides an easy way to provision and manage virtual machines on IBM PowerVM based systems in a private or hybrid cloud setting. It comes in two versions, a standard edition and a cloud edition.
This course aims to provide an overall understanding of how to install and configure IBM PowerVC Standard Edition and IBM PowerVC for Private Cloud, in an environment with HMC and IBM PowerVM NovaLink. The hands-on lab covers exercises from the basics of installing IBM PowerVC to performing advanced administrative tasks. The course also clarifies concepts in planning, deploying, and implementing IBM PowerVC for Private Cloud and IBM PowerVM NovaLink based on technology standpoints, product architectures, and their benefits.
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This introductory course enables a new system operator to develop basic to intermediate level skills needed for day-to-day operations of the Power System with IBM i. Focus is given to using the GUI (IBM i Access Client Solutions and IBM Navigator for i) as well as 5250 emulation sessions to perform tasks including job control, monitoring, sending messages, managing systems devices, and more. Hands-on exercises reinforce the lecture topics and prepare the student to successfully operate a Power System with IBM i.
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This course is designed to give new hire IT professionals an introduction into the IBM Z environment. The IBM mainframe servers, operating systems and software products will be discussed. Through lecture and hands-on labs, this course will provide the basic skill set to jump start productivity for technical professionals who are new to the mainframe environment. The skills taught in this course can be applied across multiple mainframe job roles. This course consists of 16 lecture units and 11 lab exercises.
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This course is designed to prepare students to install and configure a highly available cluster using PowerHA System Mirror.
