This 2-day instructor-led course provides students with an understanding of some of the more advanced work management techniques found in IBM MAS Manage, Reliability Strategies, Work Order Intelligence, Dynamic Job Plans, and Process Flow Control. We will also see how to edit and create Operational dashboards and Work Queues. After learning about these concepts, practice what you have learned by doing the hands-on lab exercises.
This course teaches learners how to explore, analyze, and report on data using IBM Planning Analytics Workspace and related clients. Participants learn core Planning Analytics concepts—such as models, cubes, dimensions, views, and sets—and apply them to create interactive reports, dashboards, and formatted outputs. The course combines conceptual instruction with guided, hands-on exercises that allow learners to practice real-world tasks, including creating books and views, formatting reports, entering and spreading data, applying calculations and conditional formatting, working with sandboxes, publishing websheets, and exploring forecasting results. These exercises reinforce best practices and help learners build confidence using Planning Analytics features in practical business scenarios. The course reflects the current Planning Analytics Workspace v2.1.x environment while preserving content that remains valid from earlier v2.x releases. The course emphasizes effective analysis, reporting, collaboration, and planning techniques that learners can immediately apply in their own Planning Analytics implementations.
This course teaches modelers how to design and build a complete model using IBM Planning Analytics Workspace. Learners progress through the full modeling lifecycle, starting with an overview of Planning Analytics architecture and continuing through dimension design, cube construction, data loading, and business rule development. The course emphasizes modeling best practices and performance considerations using Planning Analytics version 2.1.x.Through a combination of instructor-led explanations and hands-on exercises, learners create and enhance a working model that reflects common planning and analysis scenarios. Topics include TurboIntegrator processes for loading and maintaining data, rules and feeders for advanced calculations, and techniques for optimizing model performance.The course also covers advanced modeling capabilities such as drill-through paths, currency conversion, and time modeling for different fiscal requirements. By the end of the course, learners will be able to build scalable, maintainable models that support planning, forecasting, and reporting use cases in Planning Analytics Workspace.
The goal of this course is to provide the student with a tangible understanding and a real hands-on experience with generative AI applications deployed and optimized for IBM Power systems. This self-paced virtual course uses video lectures, review questions, and virtual lab machine exercises to provide the student with foundational knowledge and experience about the topics covered in the course. In the lecture, the student begins by learning the basics of generative AI, and the basic components of a generative AI application, then applies these concepts to real-world examples on Power where the student learns Power offerings for AI workloads, package management fundamentals in Python, Operating System deployment strategies on Power, and Power hardware use cases. The lab exercises will start with viewing and manipulating files in a basic AI application running on IBM Power Red Hat Enterprise Linux. They will have hands-on experience identifying the components of that AI application and their connection to other components, and will add functionalities to the application that demonstrate more advanced AI application techniques like frameworks, prompt tuning, and conversation memory. Then, the students will go through the process of setting up a Python virtual environment, investigating Power hardware resources, and using the Hardware Management Console (HMC) to ensure memory and other resources are optimized for AI workloads.
In this course, you learn how to deploy IBM Verify Directory. You gain skills around deploying the software, deploying and using Virtual Directory Server, and deploying and using Federated Directory Server instead of replication. This course also provides examples of LDAP commands for adding, modifying, and deleting users from the directory.
This course is designed to provide participants with a comprehensive understanding of how to plan, deploy, configure, and manage IBM Storage Ceph in enterprise environments. Through lectures, demonstrations, and extensive hands-on exercises, students will gain practical skills for working with Ceph’s distributed storage architecture. Key topics include cluster deployment, administration, data protection, and performance optimization, as well as using Ceph for object, block, and file storage workloads. By the end of the course, students will be equipped to integrate Ceph into enterprise infrastructures and operate it effectively in production environments.
IBM Storage Defender Data Protect is a comprehensive data backup and recovery solution that supports a wide range of cloud-native, edge, and on-premises workloads at scale. It helps organizations meet governance and compliance requirements for data protection and incident response, significantly reducing operational and cyber risk.In this one-day course, students learn how to deploy and perform initial maintenance tasks for an IBM Storage Defender Data Protect cluster. Hands-on lab exercises are conducted using a Linux-based environment.
Learn the essentials of IBM Fusion - its architecture, hardware, networking, data services, UI, virtualization, and multi-cluster management. This course earns you the IBM Fusion Essentials badge: https://www.credly.com/org/ibm/badge/ibm-fusion-essentials.
This course is designed to teach you how to do important post-installation administration and configuration tasks for the IBM Cloud Pak for AIOps platform. Such tasks include user management, importing topology, configuring self-monitoring, configuring correlations, and making runbooks to expedite or automate solutions to IT problems.
This course is segmented into multiple learning modules. Module 1 is an overview discussing what RIA is and how it can help to automate tasks across a business. Module 2 is configuration & UI navigation covering how to configure API authentications in RIA and how to find the main sections of the user interface. Module 3 is basic programming in RIA covering some of the commonly used programming blocks that are combined with API blocks to create automation workflows. Module 4 is workflows covering workflows in their entirety and how they're built, saved, and published. Module 5 is integrations in workflows covering product integrations in RIA and how they're used in workflows. Module 6 is troubleshooting covering some of the more common issues with workflows in RIA and how to approach fixing them. All of these learning modules contain step by step walkthroughs that have learners demonstrate their ability to complete learning objectives in a guided session.
This course is segmented into multiple learning modules. After an introduction, each Data Insight core widget will be covered in its own module, and a few administrative tasks will round out the training.
Explore the capabilities of IBM Verify Identity Access through a course designed to support skill development in troubleshooting. Learners can engage with tools like visual diagnostics and log analysis just like technical teams often do while troubleshooting issues. The course introduces methods that may help streamline issue resolution across different deployment models. It also highlights IBM's support ecosystem, including forums and portals, as potential resources for staying informed.
This course guides learners through the process of adopting IBM Verify in their organization. It covers the Verify architecture, integration with existing deployments, user import from existing sources, and strategies for migrating and securing legacy applications.
This course guides learners through the process of customizing IBM Verify in their organization. It first covers the branding options in Verify, For organizations leveraging IBM Verify, which allow organizations to extend their brand into the authentication and user self-care cycle. Branding is the process of creating a strong, positive perception of an organization and its products or services in the mind of their consumers. The second unit explains how to plan and create a user journey orchestration, which focuses on creating intuitive and engaging user experiences, covering requirements such as account creation and registration, application requests, data privacy and consent interaction, seamless login experience routing, profile recovery, and multi-factor authentication enrollment. An orchestrated user journey helps ensure that individuals are experiencing processes that align with organizational goals to deliver optimal business outcomes while making these processes intuitive and easy to navigate.
This course guides learners through the process of customizing IBM Verify in their organization. It first covers the branding options in Verify, For organizations leveraging IBM Verify, which allow organizations to extend their brand into the authentication and user self-care cycle. Branding is the process of creating a strong, positive perception of an organization and its products or services in the mind of their consumers.The second unit explains how to plan and create a user journey orchestration, which focuses on creating intuitive and engaging user experiences, covering requirements such as account creation and registration, application requests, data privacy and consent interaction, seamless login experience routing, profile recovery, and multi-factor authentication enrollment. An orchestrated user journey helps ensure that individuals are experiencing processes that align with organizational goals to deliver optimal business outcomes while making these processes intuitive and easy to navigate.
Voice technologies are rapidly reshaping how businesses interact with customers, automate operations, and analyze conversations. Today’s AI systems can deliver fast, accurate, and natural-sounding speech capabilities across multiple languages, supporting use cases such as customer self-service, live agent assistance, real-time analytics, and more.In this course, learners will explore how to apply IBM Watson Speech to Text and Watson Text to Speech to build voice-enabled solutions tailored to their unique business needs.By the end of the course, participants will have the skills to design, customize, and integrate AI-powered voice solutions that deliver seamless, human-like interactions across multiple platforms.
Learn to effectively use the core capabilities of watsonx Assistant to plan, build, troubleshoot, and maintain a virtual assistant. This course provides an in-depth exploration of several key areas of watsonx Assistant, equipping students with the technical knowledge required to create advanced virtual assistants.
In this course, students will learn to use scientific methods, processes, and algorithms to identify patterns, trends, and insights from data – with the goal of enabling better decision-making. Students will use watsonx.ai to synthesize skills from statistics, computer science, and management information systems to analyze and interpret complex datasets. This course includes a practical component with hands-on exercises focused on collecting, preparing, mining, and visualizing data and then building a machine learning and foundation model with methods on how to deploy them.
Voice technologies are rapidly reshaping how businesses interact with customers, automate operations, and analyze conversations. Today’s AI systems can deliver fast, accurate, and natural-sounding speech capabilities across multiple languages, supporting use cases such as customer self-service, live agent assistance, real-time analytics, and more.In this course, learners will explore how to apply IBM Watson Speech to Text and Watson Text to Speech to build voice-enabled solutions tailored to their unique business needs.By the end of the course, participants will have the skills to design, customize, and integrate AI-powered voice solutions that deliver seamless, human-like interactions across multiple platforms.
In this course, the learner is guided through a realistic scenario of administering and customizing the watsonx governance console for an organization wishing to govern the lifecycles of AI initiatives. The course includes user management, profile assignment and customization, modeling real-world organization structures in the governance console, identification of model risks and associated controls, customized risk assessment using questionnaires, and building specific workflows to manage AI use cases.