This 0G09BG: Advanced Statistical Analysis Using IBM SPSS Statistics v26 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.
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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 0K09BG: Advanced Statistical Analysis Using IBM SPSS Statistics v26 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.
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This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis process. Students will learn the basics of reading data, data definition, data modification, and data analysis and presentation of analytical results. Students will also see how easy it is to get data into IBM SPSS Statistics so that they can focus on analyzing the information. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base features.
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 0K53BG: IBM SPSS Statistics Essentials v26 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 provides you with information about the functions of IBM’s DB2, a relational database manager which may be installed under a variety of operating systems on many hardware platforms.
DB2 runs under the z/OS, VM, Linux, UNIX, and Windows operating systems, to name a few.
The course includes discussion of how the DB2 products provide services. The focus is on the services DB2 provides and how we work with DB2, not on its internal workings.
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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Students will describe how the Data Masking Pack works; understand how to apply policies for different data types, understand how hash lookup policies work; create a data masking job.
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 data engineers how to build a robust, fault-tolerant data pipeline that cleans, transforms, and aggregates unorganized and messy data into databases or datasources for IBM Integrated Analytics System. This course is designed to give the participant an overview of the IBM Integrated Analytics System architecture and provide a working knowledge and understanding of the SQL and data engineering best practices.
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This course is also available as classroom course IBM Aspera Console Administration (WT012G).
This ZT012G: IBM Aspera Console Administration course is intended to teach the necessary knowledge and skills to install, configure, and use IBM Aspera Console.
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This 2 day course is designed to provide skills enablement for system administrators and product support specialists in the area of operating system based virtualization provided by Linux containers. Topics include introduction to Podman, Buildah, Docker, Kubernetes and CRI-O. Hands-on exercises reinforce the lecture material, allowing students to install and configure Linux containers.
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In this three-day course, you learn how to install, configure and administer IBM Spectrum Protect Plus v10.1.6. You begin with a review of the software capabilities, requirements, and architecture. Then, through lecture and hands-on labs, you learn how to perform the various tasks required to configure the environment on an installed virtual appliance. You customize SLA policies and make use of available options to protect virtual machines and applications, as well as the IBM Spectrum Protect Plus catalog. You monitor and manage jobs, plan and prepare for disaster recovery, view log files, and create custom reports.
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This course focuses on reviewing concepts of data science, where participants will learn the stages of a data science project. Topics include using automated tools to prepare data for analysis, build models, evaluate models, and deploy models. To learn about these data science concepts and topics, participants will use IBM SPSS Modeler as a tool.
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 gets you up and running with a set of procedures for analyzing time series data. Learn how to forecast using a variety of models, including regression, exponential smoothing, and ARIMA, which take into account different combinations of trend and seasonality. The Expert Modeler features will be covered, which is designed to automatically select the best fitting exponential smoothing or ARIMA model, but you will also learn how to specify your own custom models, and also how to identify ARIMA models yourself using a variety of diagnostic tools such as time plots and autocorrelation plots.
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 0E038G: Advanced Predictive Modeling Using IBM SPSS Modeler v18.1.1 course presents advanced models to predict categorical and continuous targets. Before reviewing the models, data preparation issues are addressed such as partitioning, detecting anomalies, and balancing data. The participant is first introduced to a technique named PCA/Factor, to reduce the number of fields to a number of core fields, referred to as components or factors. The next units focus on supervised models, including Decision List, Support Vector Machines, Random Trees, and XGBoost. Methods are reviewed to combine supervised models and execute them in a single run, both for categorical and continuous targets.
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This 0E039G: Advanced Machine Learning Models Using IBM SPSS Modeler v18.2 course presents advanced models available in IBM SPSS Modeler. The participant is first introduced to a technique named PCA/Factor, to reduce the number of fields to a number of core factors, referred to as components or factors. The next topics focus on supervised models, including Support Vector Machines, Random Trees, and XGBoost. Methods are reviewed on how to analyze text data, combine individual models into a single model, and how to enhance the power of IBM SPSS Modeler by adding external models, developed in Python or R, to the Modeling palette.
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Clustering and Association Modeling Using IBM SPSS Modeler (v18.1) introduces modelers to two specific classes of modeling that are available in IBM SPSS Modeler: clustering and associations. Participants will explore various clustering techniques that are often employed in market segmentation studies. Participants will also explore how to create association models to find rules describing the relationships among a set of items, and how to create sequence models to find rules describing the relationships over time among a set of items.
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 0E069G: IBM SPSS Modeler Foundations v18.2 course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.
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 learning offering will tell a holistic story of Cloud Pak for Data including collaboration across an organization, which is key in this platform. Applicable to all personas. Multiple use cases will provide understanding of how organizations can benefit from Cloud Pak for Data. A variety of features will also be explored, providing students with the insight on how to use the platform. This learning is relevant for Cloud Pak for Data and Cloud Pak for Data System. This WBT contains instructional and interactive content, demonstrations and hands-on simulated exercises.
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IBM Network Performance Insight is a network performance monitoring system. It offers real-time and historical trends in network performance and interactive views of network data that help reduce network downtime and optimize network performance. Network Performance Insight provides IBM Netcool Operations Insight with comprehensive IP network device performance monitoring and traffic analysis. In this 3-day course, you learn how to install IBM Network Performance Insight and integrate it with IBM Netcool Operations Insight. This course is lab-intensive, with an emphasis on hands-on exercises.
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 3-days TOD67G: Network Performance Insight 1.3.1 – Implementation and Configuration course, you learn how to install IBM Network Performance Insight and integrate it with IBM Netcool Operations Insight. This course is lab-intensive, with an emphasis on hands-on exercises.
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. /terms
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This WF318G: Developing Applications in IBM Datacap v9.1.7 course provides technical professionals with the skills that are needed to build Datacap applications.
The course begins with an introduction to IBM Datacap. You learn about capture concepts, Datacap process, page identification methods, and architecture. You process batches for Datacap applications in the Datacap clients.
You learn about the design and components of a Datacap application. You build a Datacap application by using Forms Template in Datacap Studio and configure it. You learn how to troubleshoot a Datacap application. You configure a Datacap application to process documents of multiple page types in a single batch. You implement OCR and OMR to extract data from data fields and from multiple choice check boxes. You export data to a text file and also to an IBM FileNet Content Manager repository. You build page layouts, create virtual page blocks, and extract data from tables and label-value pairs. Through instructor-led presentations and hands-on lab exercises, you learn about the core features of IBM Datacap.
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This course is intended to teach the necessary knowledge and skills to install, configure, and use the IBM Aspera High-Speed Transfer Server.
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This WT012G: IBM Aspera Console Administration course is also available as self-paced virtual (e-learning) course IBM Aspera Console Administration (ZT012G). This option does not require any travel.
This course is intended to teach the necessary knowledge and skills to install, configure, and use IBM Aspera Console.
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This course is also available as classroom course WM156: IBM MQ V9.1 System Administration
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 recorded 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.
Note:This course does not cover any of the features of MQ for z/OS or MQ for IBM i.
