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The Emotional Logic workshop is designed to provide enlightening mindset shifts and educational activities around emotions, their purpose, and our values.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for application developers. Overview Describe the benefits of implementing a decision management solution with Operational Decision Manager.Identify the key user roles that are involved in designing and developing a decision management solution, and the tasks that are associated with each role.Describe the development process of building a business rule application and the collaboration between business and development teams.Set up and customize the Business Object Model (BOM) and vocabulary for rule authoring. Implement the Execution Object Model (XOM) that enables rule execution.Orchestrate rule execution through ruleflows. Author rule artifacts to implement business policies.Debug business rule applications to ensure that the implemented business logic is error-free.Set up and customize testing and simulation for business users.Package and deploy decision services to test and production environments.Integrate decision services for managed execution within an enterprise environment.Monitor and audit execution of decision services.Work with Operational Decision Manager features that support decision governance. This course introduces developers to IBM Operational Decision Manager V8.9.2. It teaches participants the concepts and skills required to design, develop, and integrate a business rule solution with Operational Decision Manager. This course begins with an overview of Operational Decision Manager, which is composed of two main environments: Decision Server for technical users and Decision Center for business users. The course outlines the collaboration between development and business teams during project development. Through instructor-led presentations and hands-on lab exercises, participants learn about the core features of Decision Server, which is the primary working environment for developers. Participants design decision services and work with the object models that are required to author and execute rule artifacts. Participants gain experience with deployment and execution, and work extensively with Rule Execution Server. In addition, students become familiar with rule authoring so that you can support business users to set up and customize the rule authoring and validation environments. Participants also learn how to use Operational Decision Manager features to support decision governance. Introducing IBM Operational Decision Manager Exercise: Operational Decision Manager in action Developing decision services Exercise: Setting up decision services Programming with business rules and developing object models Exercise: Working with the BOM Exercise: Refactoring Orchestrating ruleset execution Exercise: Working with ruleflows Authoring rules Exercise: Exploring action rules Exercise: Authoring action rules Exercise: Authoring decision tables Customizing rule vocabulary with categories and domains Exercise: Working with static domains Exercise: Working with dynamic domains Working with queries Exercise: Working with queries Debugging rules Exercise: Executing rules locally Exercise: Debugging a ruleset Enabling tests and simulations Exercise: Enabling rule validation Managing deployment Exercise: Managing deployment Exercise: Using Build Command to build RuleApps Executing rules with Rule Execution Server Exercise: Exploring the Rule Execution Server console Auditing and monitoring ruleset execution Exercise: Auditing ruleset execution through Decision Warehouse Working with the REST API Exercise: Executing rules as a hosted transparent decision service (HTDS) Additional course details: Nexus Humans WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

Duration 1 Days 6 CPD hours This course is intended for Report authors wanting to develop interactive report content, or content disconnected from IBM Cognos servers. In this course, participants increase their IBM Cognos Analytics experience by building interactive reports using Active Report controls, which can be distributed to and consumed by users in a disconnected environment, including mobile devices. Introduction to IBM Cognos Active Reports Examine IBM Cognos Active Reports Convert an existing report into an Active Report Add interactions in Active Reports using Active Report connections Create a basic Active Report Examine interactive behavior of Active Report controls Save a report in the IBM Cognos Analytics portal Save an Active Report to an MHT file Save an Active Report as a report template Use an Active Report as a prompt page Understand Active Report security Use Active Report Connections Examine Active Report connections Filter and select in controls using Active Report connections Examine variables Use a single variable to control multiple controls Use multiple variables to show different data in different controls Use Active Report controls to support mobile device usage Active Report Charts & Decks Add charts to active reports Understand and optimize chart behavior Examine decks and data decks Optimize use of decks Review Master Detail relationships Examine RAVE visualizations

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, and Business Process Owners/Team Leads/Power Users. In this course, students are enabled to transform Excel workbooks into captivating dashboards for executives and business users. Introduction to Dashboards Creating Interactive Dashboards Using an Embedded Excel Workbook in the Dashboard Data Visualizations with Charts Using Data in a Range Using Data in a Series Preparing Future Data by Ignoring End Blanks Dashboard Distribution Distributing a Dashboard Single Value Components Using Single Value Components Alerts Setting Up Alerts Selectors Using Selectors Setting Default Values for Selectors Selecting Multiple Items Common Components Using Images in a Dashboard Using Tables in a Dashboard Using an Interactive Calendar in a Dashboard Adding a URL to a Dashboard Components Used as Selectors Using the Chart Component as a Selector Using the Map Component as a Selector Format Options Configuring Proportional Size and Position Using Themes to Apply Formats Using Templates to Apply Formats Applying Globalization Dynamic Visability Adding Dynamic Visibility Using Formulas to Create Dynamic Visibility Creating Multi-Layer Dashboards Dashboard Design Optimization Optimizing Dashboard Design Dashboard Connection to Live Data Using Live Data Sources Setting Up an XML Connection Using Web Services to Connect to Data Using the Query Browser to Connect to Data Using the Portal Data Connection to Connect to Data Additional course details: Nexus Humans BOX310 SAP BusinessObjects Dashboards 4.1 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 BOX310 SAP BusinessObjects Dashboards 4.1 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 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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 advanced course is for Infrastructure Specialist, Senior Technical Specialist,Technical Specialist, Support Engineers, and System Architects. Overview Understand the MDM Architecture and how the Physical, Virtual and Hybrid MDM handles a service request Understand the core Workbench features available for the InfoSphere MDM Understand how MDM using OSGi for deploying customizations to the product Create a new Physical MDM Entity using the Workbench Wizard Extend an existing Physical MDM Entity using the Workbench Wizard Extend an existing Physical MDM Service using the Workbench Wizard Create a new Composite Service using a transiant object containing other existing business objects Customize and deploy a Virtual configuration Create a new Virtual Callout Handler Create a new Virtual Composite View Generate new Services based on the Virtual configuration (eSOA) Customize a Hybrid MDM implementation Understand the Adaptive Service Interface (ASI) This course is designed for anyone who wants to get an understanding of how to use and customize the InfoSphere Master Data Management using the InfoSphere MDM Workbench InfoSphere MDM Architecture . OSGi and MDM . Data Additions . Physical Data Extensions . MDM Physical Behavior Extensions . Composite Services . Adaptive Services Interface (ASI) . Virtual Data Model . Virtual Handlers . eSOA Toolkit . Hybrid MDM .

Duration 3 Days 18 CPD hours This course is intended for This intermediate course is for experienced SQL end users, application programmers, database administrators, and user support staff who need more advanced knowledge of SQL. Overview Discuss basic relational database concepts Use some of the OLAP features of DB2, such as GROUPing and RANKing functions Create tables, views and indexes Use referential integrity, check constraints and triggers Use outer joins, and join tables to themselves Use CASE expressions, and the CAST function Identify the impact of Summary Tables, Materialized Query Tables, and temporary tables Use complex subqueries Use a greater number of scalar SQL functions Use advanced SQL constructs, such as recursive SQL and table expressions Define User-Defined Distinct Types and User-Defined Functions Avoid several of the most common causes for poorly-performing SQL This course teaches you how to make use of advanced SQL techniques to access DB2 databases in different environments. This course is appropriate for customers working in all DB2 environments, specifically for z/OS, Linux, UNIX, and Windows. Introduction Identify the purpose of the clauses in the SELECT statement Describe the key differences among the IBM DB2 platforms Describe and use some of the OLAP features of DB2, such as GROUPING functions like CUBE and ROLLUP, and the RANK, DENSE_RANK and ROW_NUMBER functions Create Objects Code statements to: Create tables and views, Alter tables, Create indexes, Implement referential integrity (RI), and Define triggers and check constraints Identify impacts and advantages of referential integrity, including impacts of delete rules Identify considerations when using triggers and check constraints Define and make use of INSTEAD OF triggers Join Retrieve data from more than one table via inner and outer joins Use outer joins (LEFT, RIGHT, FULL) Use ANTI JOINS Join a table to itself Use UNION and UNION ALL Use EXCEPT and INTERCEPT CASE, CAST, Summary Tables, and Materialized Query Tables Identify when CASE expressions can be used Code CASE expressions in SELECT list and in the WHERE clause Identify when CAST specifications can be used Identify the advantages of using Summary (Materialized Query) Tables and Temporary tables Identify the advantages of using Materialized Query Tables (MQTs) Identify when and how to use Temporary tables Using Subqueries Code subqueries using the ALL, ANY/SOME, and EXISTS keywords Code correlated subqueries Choose the proper type of subquery to use in each case Scalar Functions Extend your knowledge of scalar functions which: Manipulate arithmetic data, Manipulate date values, and Manipulate character data Examples of scalar functions that are addressed in this course: SUBSTR POSSTR COALESCE/VALUE DECIMAL ROUND DIGITS CHAR DATE/TIME Table Expressions and Recursive SQL Identify reasons for using table expressions and recursive SQL Use nested and common table expressions Identify the difference between views and table expressions Code recursive SQL Control the depth of recursion when coding recursive SQL UDTs/UDFs and Performance Describe the concepts behind User-Defined Types, User-Defined Functions and Stored Procedures Predict when queries will use indexes to get better performance Identify concepts of predicate processing State introductory concepts about index structure State general best practices advice Additional course details: Nexus Humans CE131 IBM DB2 SQL Workshop for Experienced Users 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 CE131 IBM DB2 SQL Workshop for Experienced Users 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 Service providers who are designing or using VMware SD-WAN solutions or managing SD-WAN networks for customers Service providers looking to deliver a managed hybrid WAN with MPLS service Service providers transforming their MPLS networks for direct access to cloud services and increased network agility Overview By the end of the course, you should be able to meet the following objectives: Describe how VMware SASE™ solves security challenges for distributed enterprises Identify where VMware SD-WAN fits in the VMware SASE framework Describe the process for validating the installation of VMware SD-WAN Orchestrator and Gateway in a service provider environment Describe the features for monitoring and maintaining a VMware SD-WAN installation Evaluate the security features and certificate operations for managing a VMware SD-WAN installation Describe VMware SD-WAN Edge licensing and license types Describe the features of VMware Edge Network Intelligence™ Recognize VMware SD-WAN network monitoring tools for generating reports, events, and alerts Recognize the remote diagnostic actions available on VMware SD-WAN Orchestrator Troubleshoot VMware SD-WAN Orchestrator and Gateway common issues This three-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in operating and troubleshooting the VMware SD-WAN? environment for service providers.In this course, you focus on deploying and managing VMware SD-WAN for a service provider, including troubleshooting common issues. Course Introduction Introductions and course logistics Course objectives VMware SD-WAN Installation for Service Providers Describe security challenges for distributed enterprises Describe the VMware SASE solution for securing distributed enterprises Describe VMware deployment models for service providers Explain how VMware SD-WAN can help to transform MPLS networks to service-ready networks Identify resource requirements for installing VMware SD-WAN Orchestrator and Gateways Describe the procedure for installing VMware SD-WAN Orchestrator Describe the process for provisioning VMware SD-WAN Orchestrator Identify the external service dependencies for VMware SD-WAN Orchestrator Recognize disaster recovery options for SD-WAN Orchestrator Describe the disaster recovery workflow for VMware SD-WAN Orchestrator Identify the requirements for installing VMware SD-WAN Gateway instances Describe the procedure for installing VMware SD-WAN Gateway instances Describe the procedure for installing VMware SD-WAN Gateway instances on ESXi hosts identify Data Plane Development Kit support for gateway performance Describe the VMware SD-WAN Gateway deployment modes for service providers Configure a VMware SD-WAN Gateway for a service provider Assign a VMware SD-WAN Gateway for a service provider VMware SD-WAN Monitoring and Maintenance Describe VMware SD-WAN Orchestrator system health-monitoring features Describe VMware SD-WAN Orchestrator process-monitoring features Describe VMware SD-WAN Orchestrator storage-monitoring features Describe VMware SD-WAN Orchestrator database-monitoring features Describe the VMware SD-WAN Orchestrator upgrade process Describe the VMware SD-WAN Orchestrator backup and data archival processes Describe the VMware SD-WAN Orchestrator process to expand database disks Describe the VMware SD-WAN Orchestrator system metrics for monitoring Describe how systems metrics are collected for monitoring VMware SD-WAN Orchestrator Describe VMware SD-WAN Gateway additions and removals Describe the VMware SD-WAN Gateway upgrade process Describe the VMware SD-WAN Gateway validation process VMware SD-WAN Security and Edge Licensing Describe the VMware SD-WAN PKI security infrastructure Recognize VMware SD-WAN PKI authentication modes Describe VMware SD-WAN certificate operations Describe the VMware SD-WAN PKI certificate authentication configuration Describe the VMware SD-WAN PKI configuration process Compare operator and partner logins Describe the VMware SD-WAN self-signed certificate authority process Describe VMware SD-WAN certificate authority renewal and revocation Describe the VMware SD-WAN intermediate certificate authority Describe the VMware SD-WAN certificate chain of trust Describe the VMware SD-WAN Edge licensing and license types Assign and view the VMware SD-WAN Edge licenses and reports VMware SD-WAN Reporting and Diagnostics Describe the VMware SD-WAN network monitoring tools Describe the VMware SD-WAN network visibility options and controls Identify the VMware SD-WAN Orchestrator reporting features Describe and analyze VMware SD-WAN Orchestrator events View enterprise reports by operator, partner, and administrator View historical network insights and real-time reports on path visibility Describe common VMware SD-WAN alerts Describe the VMware SD-WAN heart mechanism for alerts Configure VMware SD-WAN alerts Analyze common VMware SD-WAN alerts Use standard networking tools for monitoring VMware SD-WAN Describe remote diagnostic actions available on VMware SD-WAN Orchestrator Use the remote diagnostics tools on VMware SD-WAN Orchestrator Generate remote diagnostics bundles and packet captures VMware SD-WAN Orchestrator and Gateway Troubleshooting Recognize the basic sanity checks to troubleshoot VMware SD-WAN Orchestrator Create diagnostic bundles to enable support to troubleshoot VMware SD-WAN Orchestrator Recognize the basic checks to troubleshoot VMware SD-WAN Orchestrator Troubleshoot common VMware SD-WAN Orchestrator performance issues Describe the tools available to troubleshoot VMware SD-WAN Gateway Analyze sample outputs for debugging a VMware SD-WAN Gateway issue Use Data Plane Development Kit to improve VMware SD-WAN Gateway performance VMware SD-WAN Orchestrator and Gateway Commands Recognize when and how to use VMware SD-WAN Orchestrator database-monitoring commands Recognize when and how to use the VMware SD-WAN Gateway process-monitoring commands

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.