18715 Courses

Free dog training taster session at Ruby's Yard, The Boat Yard, Slack’s Avenue, Atherstone, England, CV9 2AR. These 20 minute sessions will run a couple of times a year. Intended to give you information about my dog training courses.

Duration 3 Days 18 CPD hours This course is intended for Developers Administrators Overview Understand why Blockchain is needed and where Explore the major components of Blockchain Learn about Hyperledger Fabric v1.1 and the structure of the Hyperledger Architecture Lean the features of the Fabric model including chaincode, SDKs, Ledger, Security and Membership Services Perform comprehensive labs on writing chaincode Explore the architecture of Hyperledger Fabric v1.1 Understand and perform in depth labs on Bootstrapping the Network Gain a detailed understanding of the benefits, components and architecture of Hyperledger Composer Learn Hyperledger Explorer and Hyperledger Composer Playground Perform comprehensive labs to integrate/develop an application with Hyperledger Fabric running a smart contract Build applications on Hyperledger Fabric v1.1 This instructor-led Hyperledger training course is designed for developers and administrators who want to take a comprehensive deep dive on Hyperledger Fabric and Hyperledger Composer. This Hyperledger training course has several comprehensive labs, giving you real world experience.In 3 days, you will learn the need for blockchain applications, where blockchain is used, and about Hyperledger Fabric, the open source framework for developing blockchain applications and solutions with a modular architecture. Introduction to Blockchain Introduction to Blockchain What is Blockchain Types of network Public network Permissioned network Private network Need for Blockchain Components of Blockchain Consensus Provenance Immutability Finality Where can Blockchain be used Example on Blockchain How Blockchain Works How Blockchain Works Structure of Blockchain Block Hash Blockchain Distributed Lifecycle of Blockchain Smart Contract Consensus Algorithm Proof of Work Proof of Stake Practical Byzantine Fault Tolerance Actors of Blockchain Blockchain developer Blockchain operator Blockchain regulator Blockchain user Membership service provider Building A Small Blockchain Application Introduction to Hyperledger Fabric v1.1 Introduction to Hyperledger What is Hyperledger Why Hyperledger Where can Hyperledger be used Hyperledger Architecture Membership Blockchain Transaction Chaincode Hyperledger Fabric Features of Hyperledger Fabric Installation of prerequisite Getting Started With Fabric Model The Fabric Model Features of Fabric Model Chaincode SDKs Ledger Privacy through channels Security and Membership services Assets Consensus Components of Fabric Model Peer Orderer Certificate Authority Building your network Chaincode Chaincode Chaincode API How to write a Chaincode Lab Work Architecture of Hyperledger Fabric v1.1 Architecture of Hyperledger Fabric Transaction Ledger Nodes Peer Endorser Ordering Nodes Channels Certificate Authority Transaction Flow Lab Work Bootstrapping Bootstrapping the Network Introduction Lab Work Task 1 - Generate the crypto material for the various participants. Task 2 - Generate the genesis block for the Orderer node and start ordering service (solo node). Task 3 - Generated the configuration transaction block to create a new channel. Task 4 - Sign the configuration block and create the new channel. Task 5 - Make peers of all the organizations join the channel that we created in Task 4 Introdcution to Hyperledger Explorer Introduction To Hyperledger Explorer Block Details Peer List Chaincode List Transaction Details Installation of Hyperledger Explorer Starting the Explorer App Introduction to Hyperledger Composer Introduction Components of Hyperledger Composer Benefits of Hyperledger Composer Key Concepts Hyperledger Composer Solution Installation Hyperledger Composer Playground Hyperledger Composer Playground Introduction Playground Overview Lab Work Additional course details: Nexus Humans Hyperledger Training - Developing on Hyperledger Fabric 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 Hyperledger Training - Developing on Hyperledger Fabric 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 5 Days 30 CPD hours This course is intended for This course is intended for Developers and architects who will be developing applications for iOS devices. In this course you'll be shown a complete introduction to iPhone and iPad development, emphasizing the newest technologies and best practices for iOS. Introduction & Setup Start Here Joining the Apple iOS Developer Program Installing Xcode and the iOS SDK A Guided Tour of Xcode An Introduction to Xcode Playgrounds Swift Programming Language Swift Data Types, Constants, and Variables Swift Operators and Expressions Swift Flow Control The Swift Switch Statement An Overview of Swift Functions The Basics of Object Oriented Programming in Swift An Introduction to Swift Subclassing and Extensions Working with Array and Dictionary Collections in Swift Understanding Error Handling in Swift Views, Layouts, & Storyboards iOS Application and Development Architecture Creating an Interactive iOS App Understanding Views, Windows and the View Hierarchy An Introduction to Auto Layout in iOS Working with iOS Auto Layout Constraints in Interface Builder Implementing iOS Auto Layout Constraints in Code Implementing Cross-Hierarchy Auto Layout Constraints in iOS Understanding the iOS Auto Layout Visual Format Language Using Trait Variations to Design Adaptive User Interfaces Using Storyboards in Xcode An Overview of iOS Table Views Using Xcode Storyboards to Build Dynamic TableViews Implementing TableView Navigation Working with the iOS Stack View Class A Guide to Multitasking in iOS Implementing a Page based iOS Application using UIPageViewController Data Storage with Files, iCloud, & Databases Working with Directories in Swift on iOS Working with Files in Swift on iOS Preparing an iOS App to use iCloud Storage Managing Files using the iOS UIDocument Class Using iCloud Storage in an iOS Application Synchronizing iOS Key-Value Data using iCloud iOS Database Implementation using SQLite Working with iOS Databases using Core Data CloudKit Data Storage on iOS Touch, Taps, & Gestures An Overview of iOS Multitouch, Taps and Gestures An Example iOS Touch, Multitouch and Tap Application Detecting iOS Touch Screen Gesture Motions Identifying Gestures using iOS Gesture Recognizers iOS 3D Touch Implementing TouchID Authentication in iOS Apps Advanced View Options Drawing iOS 2D Graphics with Core Graphics Interface Builder Live Views and iOS Embedded Frameworks Using Core Graphics and Core Image iOS Animation using UIViewPropertyAnimator iOS UIKit Dynamics iOS Sprite Kit Programming iOS Multitasking, Background Transfer Service and Fetching iOS Application State Preservation and Restoration Integrating Maps into iOS Applications Getting Location Information using the iOS Core Location Framework Extensions An Introduction to Extensions in iOS An iOS Today Extension Widget Tutorial Creating an iOS Photo Editing Extension Creating an iOS Action Extension Receiving Data from an iOS Action Extension Building iOS Message Apps Using Event Kit to Create Date and Location Based Reminders Multimedia and Social Media Accessing the iOS Camera and Photo Library iOS Video Playback using AVPlayer and AVPlayerViewController An iOS Multitasking Picture in Picture Tutorial Playing Audio on iOS using AVAudioPlayer Recording Audio on iOS with AVAudioRecorder iOS Speech Recognition Introduction to SiriKit Integrating Twitter and Facebook into iOS Applications The App Store Making Store Purchases with SKStoreProductViewController Class Building In-App Purchasing into iOS Applications Configuring and Creating App Store Hosted Content for iOS In-App Purchases Preparing and Submitting an iOS Application to the App Store Additional course details: Nexus Humans iOS App Development Essentials 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 iOS App Development Essentials 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 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning 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 Deep Learning 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 Application developers who want to increase their understanding of Spring and Spring Boot and a focus on fundamentals. Overview By the end of the course, you should be able to meet the following objectives: Describe the benefits provided by Spring Boot Initialize a project using Spring Boot Starters Leverage Spring Boot's auto configuration features Create simplified backing-store solutions using Spring Data JPA Build a simple MVC application using Spring Boot, embedded Web Server and fat JARs or classic WARs Build a RESTful Web application Use Spring Security to secure Web and REST endpoints Enable and extend metrics and monitoring capabilities using Spring Boot actuator Leverage advance configuration capabilities Utilize Spring Boot enhancements to testing This course offers experience with Spring Boot and its major features, including auto-configuration, Actuator, Spring Boot testing framework and more. On completion, participants will have a foundation for creating enterprise and cloudready applications. Please note that this course is a subset of the material in our 4-day Spring: Core Training course - there is no need to take both courses. This course is recommended if you have a good working knowledge of Spring Basics (see Prerequisites) but are new to Spring Boot. Introduction to Spring Essentials Why Spring Configuration using Spring Bean creation Data Management Spring Boot Introduction Introduction to Spring Boot Features Value Proposition of Spring Boot Creating a simple Boot application using Spring Initializer website Spring Boot Dependencies, Auto-configuration, and Runtime Dependency management using Spring Boot starters How auto-configuration works Configuration properties Overriding auto-configuration Using CommandLineRunner JPA with Spring and Spring Data Quick introduction to ORM with JPA Benefits of using Spring with JPA JPA configuration in Spring Configuring Spring JPA using Spring Boot Spring Data JPA dynamic repositories Spring MVC Architecture and Overview Introduction to Spring MVC and request processing Controller method signatures Using @Controller, @RestController and @GetMapping annotations Configuring Spring MVC with Spring Boot Spring Boot packaging options, JAR or WAR Rest with Spring MVC An introduction to the REST architectural style Controlling HTTP response codes with @ResponseStatus Implementing REST with Spring MVC, @RequestMapping, @RequestBody and @ResponseBody Spring MVC?s HttpMessageConverters and automatic content negotiation Spring Security What problems does Spring Security solve? Configuring authentication Implementing authorization by intercepting URLs Authorization at the Java method level Understanding the Spring Security filter chain Spring security testing Actuators, Metrics and Health Indicators Exposing Spring Boot Actuator endpoints Custom Metrics Health Indicators Creating custom Health Indicators External monitoring systems Spring Boot Testing Enhancements Spring Boot testing overview Integration testing using @SpringBootTest Web slice testing with MockMvc framework Slices to test different layers of the application

Duration 3.5 Days 21 CPD hours This course is intended for This course is for AWS Cloud Architects with expertise in designing and implementing solutions running on AWS who now want to design for Microsoft Azure. Overview After completing this course, students will be able to: Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects who have previously designed for Amazon Web Services how to translate business requirements into secure, scalable, and reliable solutions for Azure. Introduction to Azure Subscriptions and accounts Resource groups and templates in Azure Resource Manager Azure global infrastructure Azure regions Azure Availability Zones Comparison with AWS Implement Azure Active Directory Introduction to Azure Active Directory Domains and custom domains Safety features Guest users in Azure Active Directory Manage multiple directories Comparison with AWS Implement and manage hybrid identities Introduction to Azure AD Connect Comparison with AWS Implement virtual networking Azure Virtual Network and VNet peering VPN and ExpressRoute connections Comparison with AWS Implement VMs for Windows and Linux Configure high availability Comparison with AWS Implement load balancing and network security Implement Azure Load Balancer Implement an Azure Application Gateway Implement Azure Firewall Implement network security groups and application security groups Comparison with AWS Implement container-based applications Configure Azure Kubernetes Service Publish a solution on an Azure Container Instance Comparison with AWS Implement an application infrastructure Create an App Service plan Create and configure Azure App Service Configure networking for an App Service Introduction to Logic Apps and Azure Functions Comparison with AWS Implement storage accounts Azure Storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Comparison with AWS Implement NoSQL databases Introduction to Azure Cosmos DB Consistency Select appropriate CosmosDB APIs Set up replicas in CosmosDB Comparison with AWS DynamoDB Implement Azure SQL databases Configure Azure SQL database settings Implement Azure SQL Database managed instances Configure high availability for an Azure SQL database Comparison with AWS Implement cloud infrastructure monitoring Monitor security Monitor cost Configure a Log Analytics workspace Comparison with AWS Implement and manage Azure governance solutions Assign RBAC roles Configure management access to Azure Implement and configure an Azure Policy Comparison with AWS Manage security for applications Implement Azure Key Vault Implement and configure Azure AD Managed Identities Register and manage applications in Azure AD Comparison with AWS Migration, backup, and disaster recovery management Migrate workloads Implement Azure Backup for VMs Implement disaster recovery Comparison with AWS

Duration 2 Days 12 CPD hours This course is intended for Report Authors Overview Create query models Create reports based on query relationships Introduction to dimensional data Introduction to dimensional data in reports Dimensional report context Focus your dimensional data Calculations and dimensional functions Create advanced dynamic reports This offering teaches Professional Report Authors about advanced report building techniques using relational data models, dimensional data, and ways of enhancing, customizing, managing, and distributing professional reports. The course builds on topics presented in the Fundamentals course. Activities will illustrate and reinforce key concepts during this learning activity. Create query models Build a query and connect it to a report Answer a business question by referencing data in a separate query Create reports based on query relationships Create join relationships between queries Combine data containers based on relationships from different queries Create a report comparing the percentage of change Introduction to dimensional reporting concepts Examine data sources and model types Describe the dimensional approach to queries Apply report authoring styles Introduction to dimensional data in reports Use members to create reports Identify sets and tuples in reports Use query calculations and set definitions Dimensional report context Examine dimensional report members Examine dimensional report measures Use the default measure to create a summarized column in a report Focus your dimensional data Focus your report by excluding members of a defined set Compare the use of the filter() function to a detail filter Filter dimensional data using slicers Calculations and dimensional functions Examine dimensional functions Show totals and exclude members Create a percent of base calculation Create advanced dynamic reports Use query macros Control report output using a query macro Create a dynamic growth report Create a report that displays summary data before detailed data and uses singletons to summarize information Design effective prompts Create a prompt that allows users to select conditional formatting values Create a prompt that provides users a choice between different filters Create a prompt to let users choose a column sort order Create a prompt to let users select a display type Examine the report specification Examine report specification flow Identify considerations when modifying report specifications Customize reporting objects Distribute reports Burst a report to email recipients by using a data item Burst a list report to the IBM Cognos Analytics portal by using a burst table Burst a crosstab report to the IBM Cognos Analytics portal by using a burst table and a master detail relationship Enhance user interaction with HTML Create interactive reports using HTML Include additional information with tooltips Send emails using links in a report Introduction to IBM Cognos Active Reports Examine Active Report controls and variables Create a simple Active Report using Static and Data-driven controls Change filtering and selection behavior in a report Create interaction between multiple controls and variables Active Report charts and decks Create an Active Report with a Data deck Use Master detail relationships with Decks Optimize Active Reports Create an Active Report with new visualizations

Duration 5 Days 30 CPD hours This course is intended for Developed for experienced IT Professionals working with Citrix Virtual Apps and Desktops 7.1x. Potential students include administrators, engineers, and architects responsible for the end user workspace, provisioning services environment, and overall health and performance of the solution. Overview How to configure Workspace Environment Management to improve the end user environment and virtual resource consumption Understand Zones in Citrix Virtual Apps and Desktops 7.1x and how to account for user and desktop locations and optimal connection and registration How to build and manage App Layers to minimize image sprawl with Citrix Virtual Apps and Desktops 7.1x Understand and configure HDX channels and protocols for improved performance delivering multimedia and data over network connections Get more value out of your Citrix Virtual Apps and Desktops 7.1x investment through the use of Workspace Environment Management, Provisioning Services, Application Layering, and advanced features. Students leave this course with a good understanding of how to manage more complex solutions such as multizone environments spanning multiple locations with configurations around StoreFront, the Delivery Controllers, and HDX. Students will gain the skills to improve logon times, user personalization, and resource performance through Workspace Environment Management. Also, learn to optimize management of your app and desktop images by building and combining App Layers. End the course by learning to install, configure, and manage Provisioning Services in accordance with leading practices.This course includes a voucher to take the related exam (1Y0-311 Citrix XenApp and XenDesktop 7.15 Advanced Administration) and earn your Citrix Certified Professional - Virtualization (CCP-V) certification. Implementing Redundancy and Scalability StoreFront and Citrix Gateway Site Infrastructure Machines Running the Virtual Delivery Agent Managing a Virtual Apps and Desktops Environment with Multiple Locations Zones VDA Registration in a Multi-Zone Environment Zone Preference Optimal Gateway Routing and Zones Managing StoreFront Store Subscriptions in a Multi- Location Environment StoreFront and Citrix ADC Branding Implementing Backups and Disaster Recovery Backups Disaster Recovery Considerations Disaster Recovery Process Implementing Advanced Authentication Methods Multi-factor Authentication - RADIUS & OTP Multi-factor Authentication - Smart Card Authentication Federated Authentication - ADFS, SAML, and FAS Improving App and Data Security Introduction to Application Security Preventing Jailbreak Attacks Minimizing the Impact of Attacks Securing Machines Running the Virtual Delivery Agent TLS to VDA Encryption GPOs and Citrix Policies Image Management Introduction to Troubleshooting Troubleshooting Methodology Process (Standard Slide) Resource Tools and Utilities Introduction to PowerShell Troubleshooting Access Issues Troubleshooting StoreFront Troubleshooting Citrix Gateway Troubleshooting Delivery Controller Issues Validating FMA Services Troubleshooting VDA Registration Issues Troubleshooting VDA Registration Troubleshooting HDX Connection Issues Troubleshooting HDX Connections Introduction to App Layering App Layering Introduction Architecture and How it Works Creating an OS Layer The OS Layer Creating a Platform Layer The Platform Layer Creating App Layers The App Layers Creating Elastic App and User Layers Elastic App Layering User Layers Deploying a Layered Image using Citrix Virtual Apps and Desktops Using Templates in App Layering Using Layered Images in a Citrix Virtual Apps and Desktops Site Exploring Layer Priority Layer Priority Maintaining an App Layering Environment Updating Layers Maintaining and Updating the App Layering Environment Common App Layering Considerations and Additional Resources Introduction to Workspace Environment Management (WEM) Workspace Environment Management (WEM) Introduction WEM Administration Using WEM to Centralize Managing User Resources with WEM Managing Profiles with WEM Managing Endpoints with the WEM Transformer Feature Using WEM for Performance Optimization Optimizing Machine Performance with WEM Optimizing User Experience with WEM Using WEM to Secure Environments WEM Environments Migrating and Upgrading WEM Migrating to WEM Upgrading a WEM Deployment WEM Multi-Location Considerations