3044 Software Development courses

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Solutions Architects who are new to designing and building cloud architectures Data Center Architects who are migrating from on-premises environment to cloud architectures Other IT/cloud roles who want to understand how to design and build cloud architectures Overview In this course, you will learn how to: Make architectural decisions based on AWS architectural principles and best practices Use AWS services to make your infrastructure scalable, reliable, and highly available Use AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well Architected Framework to improve architectures with AWS solutions This course covers all aspects of how to architect for the cloud over four-and-a-half-days. It covers topics from Architecting on AWS and Advanced Architecting on AWS to offer an immersive course in cloud architecture. You will learn how to design cloud architectures, starting small and working to large-scale enterprise level designs-and everything in between. Starting with the Well-Architected Framework, you will learn important architecting information for AWS services including: compute, storage, database, networking, security, monitoring, automation, optimization, benefits of de-coupling applications and serverless, building for resilience, and understanding costs Module 1: Introduction The real story of AWS Well-Architected Framework Six advantages of the cloud Global infrastructure Module 2: The Simplest Architectures S3 Glacier Choosing your regions Hands-on lab: Static Website Module 3: Adding a Compute Layer EC2 Storage solutions for instances Purchasing options such as dedicated host vs instances Module 4: Adding a Database Layer Relational vs non-relational Managed databases RDS Dynamo DB Neptune Hands-on lab: Deploying a web application on AWS Module 5: Networking in AWS Part 1 VPC CIDR and subnets Public vs private subnets NAT and internet gateway Security groups Module 6: Networking in AWS Part 2 Virtual Private Gateway VPN Direct Connect VPC peering Transit Gateway VPC Endpoints Elastic Load Balancer Route 53 Hands-on lab: Creating a VPC Module 7: AWS Identity and Access Management (IAM) IAM Identity federation Cognito Module 8: Organizations Organizations Multiple account management Tagging strategies Module 9: Elasticity, High Availability, and Monitoring Elasticity vs inelasticity Monitoring with CloudWatch, CloudTrail, and VPC Flow Logs Auto scaling Scaling databases Hands-on lab: Creating a highly available environment Module 10: Automation Why automate? CloudFormation AWS Quick Starts AWS Systems Manager AWS OpsWorks AWS Elastic Beanstalk Module 11: Deployment Methods Why use a deployment method? Blue green and canary deployment Tools to implement your deployment methods CI/CD Hands-on lab: Automating infrastructure deployment Module 12: Caching When and why you should cache your data Cloudfront Elasticache (Redis/Memcached) DynamoDB Accelerator Module 13: Security of Your Data Shared responsibility model Data classification Encryption Automatic data security Module 14: Building Decoupled Architecture Tight coupling vs loose coupling SQS SNS Module 15: Optimizations and Review Review questions Best practices Activity: Design and architecture - two trues and one lie Module 16: Microservices What is a microservice? Containers ECS Fargate EKS Module 17: Serverless Why use serverless? Lambda API Gateway AWS Step Functions Hands-on lab: Implementing a serverless architecture with AWS Managed Services Module 18: Building for Resilience Using managed services greatly increases resiliency Serverless for resiliency Issues with microservices to be aware of DDoS Hands-on lab: Amazon CloudFront content delivery and automating WAF rules Module 19: Networking in AWS Part 3 Elastic Network Adapter Maximum transmission units Global Accelerator Site to site VPN Transit Gateway Module 20: Understanding Costs Simple monthly calculator Right sizing your instances Price sensitive architecture examples Module 21: Migration Strategies Cloud migration strategies Planning Migrating Optimizing Hands-on lab: Application deployment using AWS Fargate Module 22: RTO/RPO and Backup Recovery Setup Disaster planning Recovery options Module 23: Final Review Architecting advice Service use case questions Example test questions Additional course details: Nexus Humans Architecting on AWS - Accelerator 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 Architecting on AWS - Accelerator 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 2 Days 12 CPD hours This course is intended for Security administrators who are responsible for using SaltStack SecOps to manage the security operations in their enterprise Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture of SaltStack Config and SaltStack SecOps Integrate SaltStack Config with directory services. Configure roles and permissions for users and groups to manage and use SaltStack SecOps Use targeting to ensure that the jobs run on the correct minion systems Use remote execution modules to install the packages, transfer files, manage services, and manage users on minion systems Manage configuration control on the minion systems with states, pillars, requisites, and declarations Use Jinja and YAML code to manage the minion systems with the state files Enforce the desired state across minion systems automatically Use SaltStack SecOps to update the compliance and vulnerability content libraries Use SaltStack SecOps to enforce compliance and remediation on the infrastructure with industry standards Use SaltStack SecOps to provide automated vulnerability scanning and remediation on your infrastructure This two-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in using VMware vRealize© Automation SaltStack© SecOps. SaltStack SecOps allows you to scan your system for compliance against security benchmarks, detect system vulnerabilities, and remediate your results. This course enables you to create the SaltStack SecOps custom compliance libraries and use SaltStack SecOps. In addition, this course provides you with the fundamentals of how to use VMware vRealize© Automation SaltStack© Config to install software and manage system configurations. Course Introduction Introductions and course logistics Course objectives SaltStack Config Architecture Identify the SaltStack Config deployment types Identify the components of SaltStack Config Describe the role of each SaltStack Config component SaltStack Config Security Describe local user authentication Describe LDAP and Active Directory authentication Describe the roles and permissions in vRealize Automation for SaltStack Config Describe the roles and permissions in SaltStack Config Describe the SecOps permissions in SaltStack Config Describe the advanced permissions available in SaltStack Config Targeting Minions Describe targeting and its importance Target minions by minion ID Target minions by glob Target minions by regular expressions Target minions by lists Target minions by compound matching Target minions by complex logical matching Remote Execution and Job Management Describe remote execution and its importance Describe functions and arguments Create and manage jobs Use the Activities dashboard Configuration Control Through States, Pillars, Requisites, and Declarations Define the SaltStack states Describe file management in SaltStack Config Create the SaltStack state files Identify the components of a SaltStack state Describe pillar data and the uses of pillar data Configure pillar data on the SaltStack Config master server Use pillar data in variables in the state files Describe the difference between IDs and names in the state files Use the correct execution order Use requisites in the state files Using Jinja and YAML Describe the SaltStack Config renderer system Use YAML in the state files Use Jinja in the state files Use Jinja conditionals, lists, and loops Using SaltStack SecOps Comply Describe the SaltStack SecOps Comply architecture Describe CIS and DISA STIG benchmarks Describe the SaltStack SecOps Comply security library Describe the remediation differences between SaltStack SecOps and VMware Carbon Black© Create and manage the policies Create and manage the custom checks Run assessments on the minion systems Use SaltStack SecOps to remediate the noncompliant systems Manage the SaltStack SecOps Comply configuration options Manage the benchmark content ingestion Using SaltStack SecOps Protect Describe Common Vulnerabilities and Exposures (CVEs) Use the Protect dashboard Create and manage the policies Update the vulnerability library Run the vulnerability scans Remediate the vulnerabilities Manage the vulnerability exemptions

Duration 5 Days 30 CPD hours This course is intended for This course is intended for IT Professionals who are already experienced in general Windows Server and Windows Client administration, and who want to learn more about using Windows PowerShell for administration. No prior experience with any version of Windows PowerShell, or any scripting language, is assumed. This course is also suitable for IT Professionals already experienced in server administration, including Exchange Server, SharePoint Server, SQL Server, System Center, and others. Overview After completing this course, students will be able to: Describe the functionality of Windows PowerShell and use it to run and find basic commands. Identify and run cmdlets for server administration. Work with Windows PowerShell pipeline. Describe the techniques Windows PowerShell pipeline uses. Use PSProviders and PSDrives to work with other forms of storage. Query system information by using WMI and CIM. Work with variables, arrays, and hash tables. Write basic scripts in Windows PowerShell. Write advanced scripts in Windows PowerShell. Administer remote computers. Use background jobs and scheduled jobs. Use advanced Windows PowerShell techniques. This course provides students with the fundamental knowledge and skills to use Windows PowerShell for administering and automating administration of Windows based servers. Getting Started with Windows PowerShell Overview and Background Understanding command syntax Finding commands Lab : Configuring Windows PowerShell Lab : Finding and Running Basic Commands Cmdlets for administration Active Directory administration cmdlets Network configuration cmdlets Other server administration cmdlets Lab : Windows Administration Working with the Windows PowerShell pipeline Understanding the Pipeline Selecting, Sorting, and Measuring Objects Filtering Objects Out of the Pipeline Enumerating Objects in the Pipeline Sending pipeline data as output Lab : Using the Pipeline Lab : Filtering Objects Lab : Enumerating Objects Lab : Sending output to a file Understanding How the Pipeline Works Passing the pipeline data Advanced considerations for pipeline data Lab : Working with Pipeline Parameter Binding Using PSProviders and PSDrives Using PSProviders Using PSDrives Lab : Using PSProviders and PSDrives Querying Management Information by Using WMI and CIM Understanding WMI and CIM Querying Data with WMI and CIM Making changes with WMI/CIM Lab : Working with WMI and CIM Working with variables, arrays, and hash tables Using variables Manipulating variables Manipulating arrays and hash tables Lab : Working with variables Basic scripting Introduction to scripting Scripting constructs Importing data from files Lab : Basic scripting Advanced scripting Accepting user input Overview of script documentation Troubleshooting and error handling Functions and modules Lab : Accepting data from users Lab : Implementing functions and modules Administering Remote Computers Using basic Windows PowerShell remoting Using advanced Windows PowerShell remoting techniques Using PSSessions Lab : Using basic remoting Lab : Using PSSessions Using Background Jobs and Scheduled Jobs Using Background Jobs Using Scheduled Jobs Lab : Using Background Jobs and Scheduled Jobs Using advanced Windows PowerShell techniques Creating profile scripts Using advanced techniques Lab : Practicing advanced techniques Lab : Practicing script development (optional)

Duration 2 Days 12 CPD hours This course is intended for This course is intended for SQL Server administrators who work in a Windows network environment. At least one year of experience administering SQL Servers and using PowerShell is recommended. Overview After completing this course, students will be able to: •Install and Configure SQL Server and all its components using PowerShell •Manage day-to-day SQL Server Administration with PowerShell •Maintain the SQL Server environment using PowerShell scripting and programming options This course provides candidates with the knowledge and skills needed to use PowerShell for SQL Server administration. Students will learn how to manage day-to-day and scheduled maintenance tasks. Install and Configure SQL Server with PowerShell Install SQL Server Configure Database Settings Configure SQL Server Settings Configure SQL Server Policy-Based Management Lab 1: Configuring SQL Server with PowerShell Administering SQL Servers with PowerShell Managing Users and Roles Managing Database Performance Managing Database Availability Managing SQL Server Features Lab 1: Administering SQL Servers with PowerShell Maintaining SQL Server with PowerShell Managing Backups and Restores Maintaining Database Integrity and Performance Monitoring and Auditing Task Automation Generating Reports Lab 1: Maintaining SQL Servers with PowerShell

Duration 5 Days 30 CPD hours This course is intended for This course is intended for IT Professionals who are already experienced in general Windows Server and Windows Client administration, and who want to learn more about using Windows PowerShell for administration. No prior experience with any version of Windows PowerShell, or any scripting language, is assumed. This course is also suitable for IT Professionals already experienced in server administration, including Exchange Server, SharePoint Server, SQL Server, System Center, and others. Overview After completing this course, students will be able to:Describe the functionality of Windows PowerShell and use it to run and find basic commands.Identify and run cmdlets for server administration.Work with Windows PowerShell pipeline.Describe the techniques Windows PowerShell pipeline uses.Use PSProviders and PSDrives to work with other forms of storage.Query system information by using WMI and CIM.Work with variables, arrays, and hash tables.Write basic scripts in Windows PowerShell.Write advanced scripts in Windows PowerShell.Administer remote computers.Use background jobs and scheduled jobs.Use advanced Windows PowerShell techniques. This course provides students with the fundamental knowledge and skills to use Windows PowerShell for administering and automating administration of Windows based servers. Getting Started with Windows PowerShell Overview and Background Understanding command syntax Finding commands Lab : Configuring Windows PowerShell Lab : Finding and Running Basic Commands Cmdlets for administration Active Directory administration cmdlets Network configuration cmdlets Other server administration cmdlets Lab : Windows Administration Working with the Windows PowerShell pipeline Understanding the Pipeline Selecting, Sorting, and Measuring Objects Filtering Objects Out of the Pipeline Enumerating Objects in the Pipeline Sending pipeline data as output Lab : Using the Pipeline Lab : Filtering Objects Lab : Enumerating Objects Lab : Sending output to a file Understanding How the Pipeline Works Passing the pipeline data Advanced considerations for pipeline data Lab : Working with Pipeline Parameter Binding Using PSProviders and PSDrives Using PSProviders Using PSDrives Lab : Using PSProviders and PSDrives Querying Management Information by Using WMI and CIM Understanding WMI and CIM Querying Data with WMI and CIM Making changes with WMI/CIM Lab : Working with WMI and CIM Working with variables, arrays, and hash tables Using variables Manipulating variables Manipulating arrays and hash tables Lab : Working with variables Basic scripting Introduction to scripting Scripting constructs Importing data from files Lab : Basic scripting Advanced scripting Accepting user input Overview of script documentation Troubleshooting and error handling Functions and modules Lab : Accepting data from users Lab : Implementing functions and modules Administering Remote Computers Using basic Windows PowerShell remoting Using advanced Windows PowerShell remoting techniques Using PSSessions Lab : Using basic remoting Lab : Using PSSessions Using Background Jobs and Scheduled Jobs Using Background Jobs Using Scheduled Jobs Lab : Using Background Jobs and Scheduled Jobs Using advanced Windows PowerShell techniques Creating profile scripts Using advanced techniques Lab : Practicing advanced techniques Lab : Practicing script development (optional)

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS 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 The Machine Learning Pipeline on AWS 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 course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Architecture and course review Post course knowledge check Architecture review Course review

Duration 1 Days 6 CPD hours In this hands on workshop for Agile Scrum Masters, Release Train Engineers and anyone serving as Jira Administrators, Jira experts will lead you through advanced configuration and customization settings in Jira, from installation through to customized screens, workflows, filters and reports. Jira Administration Adding and managing Users Administering and managing Groups Global Jira Settings Jira layout and interface customization User authentication and security Jira Customization Customization of screens and fields Customization of workflows Project and Board Administration Configuring and managing Projects Configuring and managing Boards Creating and managing Filters JQL Jira Integration Integrating Jira with Atlassian Tools Retrospectives and Documentation in Confluence Code management with Bitbucket Integration management with Bamboo Building a Dashboard with gadgets Jira Plug-ins and Marketplace

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures. Module 1: Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Module 2: Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Module 3: Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Module 4: Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Module 5: Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Module 6: Architecture and course review Post course knowledge check Architecture review Course review Additional course details: Nexus Humans Building Data Lakes on AWS 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 Building Data Lakes on AWS 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 2 Days 12 CPD hours This course is intended for This intermediate course is for Business and Technical Specialist working with the Matching, Linking, and Search services of InfoSphere MDM Virtual module. Overview Understand how Matching and Linking work for both the Virtual Implementations of InfoSphere MDM Understand the MDM configuration project and database tables used by the PME Understand the PME Algorithms (Standardization, Bucketing and Comparison steps) and how to create and customize the algorithms using the workbench Understand how to analyze the Bucketing steps in an algorithm Understand how to generate weights for a given algorithm and how those weights are generated based on a sample database set Understand how to analyze the weights that are generated using the workbench Understand how to deploy the PME configuration for the Virtual implementations of InfoSphere MDM The InfoSphere MDM Virtual Module Algorithms V.11 course prepares students to work with and customize the algorithm configurations deployed to the InfoSphere MDM Probabilistic Matching Engine (PME) for Virtual MDM implementations. PME and Virtual Overview Virtual MDM Overview Terminology (Source, Entity, Member, Attributes) PME and Virtual MDM ( Algorithms, Weights, Comparison Scores, Thresholds) Virtual MDM Linkages and Tasks Virtual MDM Algorithms Standardization Bucketing Comparison Functions Virtual PME Data Model Algorithm configuration tables Member Derived Data Bucketing Data Bucket Analysis Analysis Overview Attribute Completeness Bucket Analysis Weights Weights Overview (Frequency-based weights, Edit Distance weights and Parameterize weights) The weight formula Running weight generation Analyzing weights Bulk Cross Match process Pair Manager Threshold calculations Additional course details: Nexus Humans ZZ880 IBM Virtual Module Algorithms for InfoSphere MDM V11 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 ZZ880 IBM Virtual Module Algorithms for InfoSphere MDM V11 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.