105 Courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for This course is designed for technical professionals who require the skills to administer IBM MQ. Overview After completing this course, you should be able to: Describe the IBM MQ deployment options Create and manage queue managers, queues, and channels Use the IBM MQ sample programs and utilities to test the IBM MQ network Configure distributed queuing Configure MQ client connections to a queue manager Define and administer a queue manager cluster Administer Java Message Service (JMS) in MQ Implement basic queue manager restart and recovery procedures Use IBM MQ troubleshooting tools to identify the cause of a problem in the IBM MQ network Manage IBM MQ security Monitor the activities and performance of an IBM MQ system This course is also available as self-paced virtual (e-learning) course IBM MQ V9.1 System Administration (ZM156G). This option does not require any travel.This course teaches you how to customize, operate, administer, and monitor IBM MQ on-premises on distributed operating systems. The course covers configuration, day-to-day administration, problem recovery, security management, and performance monitoring. In addition to the instructor-led lectures, the hands-on exercises provide practical experience with distributed queuing, working with MQ clients, and implementing clusters, publish/subscribe messaging. You also learn how to implement authorization, authentication, and encryption, and you learn how to monitor performance. Introducing IBM MQ Exercise Getting started with IBM MQ Working with IBM MQ administration tools Exercise Working with IBM MQ administration tools Configuring distributed queuing Exercise Implementing distributed queuing Managing clients and client connections Exercise Connecting an IBM MQ client Advanced IBM MQ client features Working with queue manager clusters Exercise Implementing a basic cluster Publish/subscribe messaging Exercise Configuring publish/subscribe message queuing Implementing basic security in IBM MQ Exercise Controlling access to IBM MQ Securing IBM MQ channels with TLS Exercise Securing channels with TLS Authenticating channels and connections Exercise Implementing connection authentication Supporting JMS with IBM MQ Diagnosing problems Running an IBM MQ trace Backing up and restoring IBM MQ messages and object definitions Using a media image to restore a queue Backing up and restoring IBM MQ object definitions High availability Monitoring and configuring IBM MQ for performance Monitoring IBM MQ for performance Monitoring resources with the IBM MQ Console Additional course details: Nexus Humans WM156G IBM MQ V9.1 System Administration (using Windows for labs) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the WM156G IBM MQ V9.1 System Administration (using Windows for labs) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This lecture and exercise-based course is for individuals who want to understand how to install, configure, and manage an IBM Spectrum Scale storage cluster. Overview After completing this course, you should be able to: Summarize the key features of IBM Spectrum Scale Describe IBM ESS and Spectrum Scale RAID Install IBM Spectrum Scale and configure a cluster Manage a cluster Implement information lifecycle management (ILM) Configure IBM Spectrum Scale high availability features Back up critical cluster data This course is intended for IT professionals tasked with administering an IBM Spectrum Scale storage cluster in environments running Linux and AIX nodes. The course includes information on installing, configuring, and monitoring an IBM Spectrum Scale cluster. Many Spectrum Scale features are described in lecture materials and then implemented in lab exercises. These features include: Storage management, high availability options, cluster management, and information lifecycle management (ILM) tools. Note: Although the lab environment is running the Linux operating system, the differences in Spectrum Scale compared with an AIX environment are minor. Therefore, the skills acquired during the course can be applied in both Linux and AIX environments. Welcome and course overview Unit 1 - IBM Spectrum Scale overview Exercise 1 - Cluster node preparation Unit 2 - Installation and cluster configuration Exercise 2 - Installation and cluster configuration Unit 3 - Cluster management Exercise 3 - Cluster management and configuration Unit 4 - Information Lifecycle Management (ILM) Exercise 4 - Storage pools, filesets, and policies Unit 5 - High availability and cluster data backups Exercise 5 - Replication and snapshots Course wrap-up and evaluation

Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1.5 Days 9 CPD hours This course is intended for This course is designed for WebSphere administrators who have experience with stand-alone application server environments, and want to learn about creating and managing a federated environment. Overview After completing this course, you should be able to: Describe the architectural concepts that are related to WebSphere Application Server Network Deployment Create a deployment manager instance Federate an application server to a cell Add a stand-alone application server to a WebSphere Application Server cell Cluster an application server within a WebSphere Application Server cell Configure WebSphere Application Server SSL security settings Deploy applications in clustered environments Describe the features of Intelligent Management This course teaches you the skills that are needed to administer IBM WebSphere Application Server V9 in a federated environment.This release of IBM WebSphere Application Server provides enhanced support for standards (notably Java 7 EE), emerging technology, and a choice of development frameworks.In this course, you learn how to configure and maintain IBM WebSphere Application Server V9 Network Deployment. You learn how to deploy and create a deployment manager and federate a cell. In addition, you learn how to create a cluster within the federated cell.Throughout the course, hands-on exercises and demonstrations reinforce lecture content. You gain practicalexperience with WebSphere Application Server V9 by completing tasks such as creating a deployment manager, federating a stand-alone application server, creating a custom profile, and clustering an existing application server. Course Introduction WebSphere Application Server architecture: Federated Federating a cell Exercise: Configuring the lab workstation Exercise: Creating a federated cell Workload management Exercise: Clustering and workload management WebSphere security: SSL Exercise: Configuring SSL for WebSphere Overview of Intelligent Management Course summary

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