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Duration 5 Days 30 CPD hours This course is intended for Network EngineersSystems EngineersNetwork OperatorsNetwork Administrators Overview Upon completion of this course, students will be able to:Successfully configure and deploy ClearPass for policy management, AAA, network access control and reporting.Using the ClearPass GUI, you should become familiar with how to setup authentication services, add users and devices and perform administration tasks. The ClearPass Essentials course provides you with a foundation in Network Access Control using ClearPass product portfolio. This course covers in depth configuration of ClearPass policy manager with a focus on Enforcement and Device Profiling. Intro to ClearPassClearPass for AAAExternal AuthenticationGuestOnboardEndpoint AnalysisPostureOperations & Admin UsersClustering & RedundancyLicensingClearPass ExchangeFinal Case Study

Duration 4 Days 24 CPD hours This course is intended for This course is designed primarily for network and software engineers who are interested in learning about automation and programmability and hold the following job roles: Network administrators Solutions designers System installers System integrators System administrators Overview After completing this course, you should be able to: Explain the transactional service activation and how it relates to business requirements Explain how Cisco NSO communicates with network devices Understand the NETCONF protocol and be able to read and write simple YANG models Understand the difference between devices that are fully NETCONF capable and those that are less or not NETCONF capable Understand the support for candidate configuration and confirmed commit support Use logs to troubleshoot the Cisco NSO deployment and check NSO communication with network devices Explain the YANG service model structure Design a real-world usable service Explain the mapping logic of service parameters to device models and consequently to device configurations Describe the use of different integration options and APIs Explain how to implement action with use of config-templates in NSO package Explain the use of Reactive FASTMAP in for manipulating and implementing advanced NFV components Describe the use of feature components and function packs Define and explain the ETSI MANO principles and solution Work with the alarm console, and understand the NSO alarm structure and how it conforms to modern network operations procedures Describe Cisco NSO 5.3 new features and changes in NSO The NSO Essentials for Programmers and Network Architects (NSO201) v4.1 course introduces you to Cisco Network Services Orchestrator (NSO). You will learn to install Cisco NSO and use it to manage devices and create services based on YANG templates with XPath. This course provides an overview of NSO as a network automation solution as well as introducing you to NETCONF, YANG, and XPath. You will learn about managing devices and creating device templates, service management and service package creation, network element drivers, interfacing with other systems using APIs, configuring and troubleshooting system settings, managing alarms and reporting, configuring NSO for scalability and performance, and capabilities that can be added to Cisco NSO. Course Outline Introducing Service Orchestration with Cisco NSO Exploring Cisco NSO Architecture Orchestrating Network Solutions Describing Cisco NSO Operation Installing Cisco NSO Exploring the Advantages of NETCONF Managing Devices Using the Device Manager Creating YANG Models Using Services Implementing Services with Model-to-Model Mapping Designing Services in Cisco NSO Managing the Service Lifecycle Programming with Python in Cisco NSO Configuring and Troubleshooting System Settings Discovering Cisco NSO Northbound APIs Managing Alarms and Reporting Configuring Cisco NSO for Scalability and Performance Describing Cisco NSO VNF Manager and Function Packs

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Duration 3 Days 18 CPD hours Overview ?The OS X Sierra troubleshooting process?How to use OS X Sierra tools and resources to troubleshoot OS X Sierra?OS X Sierra features and functionality, including how to find more information about OS X Sierra?How to prepare for Apple Certified Support Professional (ACSP) 10.12 certification In this course students will receive an in-depth exploration of troubleshooting on OS X Sierra. Installation and Configuration Install OS X Sierra Setup and Configuration OS X Recovery OS X Software Updates User Accounts User Accounts User Home Folders System Security Keychain Management File Systems File Systems and Storage FileVault 2 Permissions and Sharing File System Troubleshooting SIP Data Management Hidden Items and Shortcuts System resources Metadata and Spotlight File Archives Time Machine Applications and Processes Application Installation Document Management Application Management and Troubleshooting Network Configuration Network Essentials Advanced Network Configuration Network Troubleshooting Network Services Network Services Host Sharing and Personal Firewall System Management Peripherals and Drivers Print and Scan System Troubleshooting Additional course details: Nexus Humans Sierra 101 - OS X Support Essentials 10.12 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 Sierra 101 - OS X Support Essentials 10.12 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 designed for integration developers who configure service policies on IBM© DataPower Gateways. Overview After completing this course, you should be able to: Describe how DataPower gateways are configured Create and configure cryptographic objects Configure Secure Sockets Layer (SSL) to and from DataPower gateways Configure a multi-protocol gateway (MPGW) to handle multiple protocols from a single service Configure a service level monitoring (SLM) policy to control message traffic Use logs and probes to troubleshoot services Use patterns to define and deploy new services Configure message transformation and routing by using style sheets (XSL) and GatewayScripts Handle errors in service policies This course teaches you the essential skills that are required to configure, implement, and troubleshoot services that are developed on the IBM© DataPower Gateways (IDG) with firmware version 7.5.0, regardless of use case. The DataPower Gateways allow an enterprise to simplify, accelerate, and enhance the security capabilities of its XML and web services deployments, and extend the capabilities of its service-oriented architecture (SOA) infrastructure. The gateways also extend these capabilities into the JSON, REST, and Mobile application areas. Through a combination of instructor-led lectures and hands-on lab exercises, you learn how to develop and debug services that are implemented on the DataPower gateways. These skills include WebGUI and Blueprint Console navigation, service type selection, basic multi-protocol gateway configuration, creating and using cryptographic objects, and configuring SSL connections. You also learn how to use various problem determination tools such as logs, monitors, and probes, and techniques for testing DataPower services and handling errors. Hands-on exercises give you experience working directly with a DataPower Gateway. The exercises focus on skills such as creating multi-protocol gateways, working with cryptographic and SSL objects, configuring service level monitoring, troubleshooting services, handling errors in a service policy, and deploying a service from a pattern. Course introductionQuick introduction to developing on DataPowerExercise: First exposure to the DataPower developer environmentServices overviewStructure of a serviceExercise: Creating a BookingService gatewayMulti-protocol gateway serviceProblem determination toolsExercise: Enhancing the BookingService gatewayHandling errors in a service policyExercise: Adding error handling to a service policyDataPower cryptographic tools and SSL setupExercise: Creating cryptographic objects and configuring SSLService level monitoringExercise: Implementing a service level monitor in a multi-protocol gatewayPatterns for service configurationExercise: Using a DataPower pattern to deploy a serviceCourse summary

Duration 4 Days 24 CPD hours This course is intended for This basic course is for business data analysts who want to profile and assess data using Information Analyzer, also data quality analysts who need to measure data quality. Overview Analyze data structures to determine agreement with documented metadataDiscover data anomaliesIdentify invalid and incomplete data valuesDetermine potential primary keys to table structuresAdd business meaning to dataProduce deliverables that can be used by business users and ETL developersConfigure Information AnalyzerAdminister the Information Analyzer environmentUnderstand security considerations around data analysisUnderstand the methodology supporting data analysisUse Information Analyzer to analyze data content and structureUse Information Analyzer to construct data rules and utilize IBM-supplied data rule templates In this course, you will learn how to use the IBM InfoSphere suite to analyze data and report results to business users. Course Outline Information Analysis concepts Information Server overview Information Analyzer overview Information Analyzer Setup Column analysis Concepts Basic data profiling techniques in practice Data profiling techniques Primary key analysis Concepts Basic data profiling techniques in practice Foreign key and cross domain analysis Concepts Basic data profiling techniques in practice Baseline analysis Reporting and publishing Extending the meta data using Information Governance Catalog and Information Analyzer Data Rules and Metrics Additional course details: Nexus Humans KM803 IBM Information Analyzer Essentials v11.5 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 KM803 IBM Information Analyzer Essentials v11.5 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 Data Analysts responsible for data quality using QualityStageData Quality ArchitectsData Cleansing Developers Overview List the common data quality contaminantsDescribe each of the following processes: Investigation, Standardization, Match. & SurvivorshipDescribe QualityStage architectureDescribe QualityStage clients and their functionsImport metadataBuild and run DataStage/QualityStage jobs, review resultsBuild Investigate jobsUse Character Discrete, Concatenate, and Word Investigations to analyze data fieldsDescribe the Standardize stageIdentify Rule SetsBuild jobs using the Standardize stageInterpret standardization resultsInvestigate unhandled data and patternsBuild a QualityStage job to identify matching recordsApply multiple Match passes to increase efficiencyInterpret and improve match resultsBuild a QualityStage Survive job that will consolidate matched records into a single master recordBuild a single job to match data using a Two-Source match This course teaches how to build QualityStage parallel jobs that investigate, standardize, match, and consolidate data records. Students will gain experience by building an application that combines customer data from three source systems. Data Quality Issues Listing the common data quality contaminants Describing data quality processes QualityStage Overview Describing QualityStage architecture Describing QualityStage clients and their functions Developing with QualityStage Importing metadata Building DataStage/QualityStage Jobs Running jobs Reviewing results Investigate Building Investigate jobs Using Character Discrete, Concatenate, and Word Investigations to analyze data fields Reviewing results Standardize Describing the Standardize stage Identifying Rule Sets Building jobs using the Standardize stage Interpreting standardize results Investigating unhandled data and patterns Match Building a QualityStage job to identify matching records Applying multiple Match passes to increase efficiency Interpreting and improving Match results Survive Building a QualityStage survive job that will consolidate matched records into a single master record Two-Source Match Building a QualityStage job to match data using a reference match Additional course details: Nexus Humans KM213 IBM InfoSphere QualityStage Essentials v11.5 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 KM213 IBM InfoSphere QualityStage Essentials v11.5 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 New users of IBM SPSS Statistics Users who want to refresh their knowledge about IBM SPSS Statistics Anyone who is considering purchasing IBM SPSS Statistics Overview Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables. Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders Additional course details: Nexus Humans 0G53BG IBM SPSS Statistics Essentials (V26) 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 0G53BG IBM SPSS Statistics Essentials (V26) 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.

I'd like to invite you to my workshop where we will be sharing the uses and benefits of using doTERRA essential oils for autism and sensory needs disorders, this workshop is not where we diagnose a treatment or cure for autism, we always recommend you to speak to a medical professional, but it is a workshop where we can learn, share and experience how customers and colleagues in our community have been using essential oils to support their children and themselves. You will learn how safe, and effective essential oils are and you will learn ideas that have been successfully used by both parents and children. We recognise and will discuss something we call 'triggers', example 'triggering' situations, a visit to the supermarket or getting dressed, a change to routine. How essential oils can be used daily as a routine and when to use them when there are signs of a 'trigger'. Also, suggestions that can help when full blow 'triggers' are happening, often referred to as 'meltdown'. Essential oils are not only supportive, but they are also empowering. If you would like to learn more, come along to my FREE workshop. Please note, this class is for my existing customers of our team and for those new to doTERRA essential oils. If you already have an account then please speak to those that introduced you to doTERRA about this topic and available workshops, if you aren't sure, then please reach out and I will try to help you. jackie.purpletrain@outlook.com

Duration 1 Days 6 CPD hours This course is intended for This course is for solution architects, solution designers, administrators, product managers, or anyone who needs to learn the essentials of IBM Case Manager. Overview Describe the users of IBM Case Manager Identify components of IBM Case Manager Create and process a case Search for a case Review a case Add annotations and comments to a case Split a case Explore and identify the structure of a solution Add a custom task Add a quick task Identify IBM Case Manager integration options This course is an introduction to IBM Case Manager, concepts, functions, and architecture. Participants use an IBM Case Manager system to practice the skills that are required by case workers to process cases and create runtime tasks. Introduction to IBM Case Manager Describe the uses of IBM Case Manager Identify components of IBM Case Manager Create and process a case Identify a case List the components of a case type Describe the IBM Case Manager Client Add a case and process a work item Review a case Search for a case Review a case Add annotations and comments to a case Split a case Structure of a solution Describe IBM Case Manager solutions and their assets Identify IBM Case Manager environments Explore the IBM Case Manager Builder Step Designer Add runtime tasks Add a custom task Add a quick task IBM Case Manager integration options Identify IBM Case Manager integration options