20447 Disc courses

Duration 5 Days 30 CPD hours This course is intended for network professionals who are looking to build their foundational knowledge of the ClearPass product portfolio This training combines the following classes into one five day workshop, preparing you for the ACCP certification: ACF-Aruba ClearPass Fundamentals IAC-Implementing Aruba ClearPass Overview Ability to setup ClearPass as a AAA server Demostrate Configuration Guest, Ongurad, Onboard and Profiling features Integrate with External AD Server Understand Monitoring and Reporting Demostrate Scaling and deployment of best practices It prepares participants with foundational skills in Network Access Control using the ClearPass product portfolio. This 5-day classroom session includes both modules and labs to teach participants about the major features of the ClearPass portfolio Intro to ClearPass BYOD High Level Overview Posture and Profiling Guest and Onboard ClearPass for AAA Policy Service Rules Authentication Authorization and Roles Enforcement Policy and Profiles Authentication and Security Concepts Authentication Types Servers Radius COA Active Directory Certificates Intro to NAD NAD Devices Adding NAD to ClearPass Network Device Groups Network Device Attributes Aruba Controller as NAD Aruba Switch Aruba Instant Monitoring and Troubleshooting Monitoring Troubleshooting Logging Policy Simulation ClearPass Insight Insight Dashboard Insight Reports Insight Alerts Insight Search Insight Administration Insight Replication Active Directory Adding AD as Auth Source Joining AD domain Using AD services External Authentication Multiple AD domains LDAP Static Host Lists SQL Database External Radius Server Guest Guest Account creation Web Login pages Guest Service configuration Self-registration pages Configuring NADS for Guest Guest Manager Deep Dive Web Login Deep Dive Sponsor Approval MAC Caching Onboard Intro to Onboard Basic Onboard Setup Onboard Deepdive Single SSID Onboarding Dual SSID Onboarding Profiling Intro to Profiling Endpoint Analysis Deep Dive Posture Intro to Posture Posture Deployment Options OnGuard Agent Health Collection OnGuard workflow 802.1x with Posture using Persistent/dissolvable agent OnGuard web LoginMonitoring and Updates Operation and Admin Users Operations Admin Users Clustering and Redundancy Clustering Redundancy LAB Licensing ClearPass Licensing Base License Applications Single Sign-On Deployment Options ClearPass Admin Login SSO Access Network SSO ASO-Auto-Sign On Configuration and Demo ClearPass Exchange Intro Examples General HTTP Palo Alto Firewall Configuration Case Study Objectives Discussion Advanced Labs Overview

Duration 2 Days 12 CPD hours This course is intended for The audience for this course is data professionals and data architects who want to learn about migrating data platform technologies that exist on Microsoft Azure and how existing SQL based workloads can be migrated and modernized. The secondary audience for this course is individuals who manage data platforms or develop applications that deliver content from the existing data platform technologies. Overview Understand Data Platform Modernization Choose the right tools for Data Migration Migrate SQL Workloads to Azure Virtual Machines Migrate SQL Workloads to Azure SQL Databases Migrate SQL Workloads to Azure SQL Database Managed Instance In this course, the students will explore the objectives of data platform modernization and how it is suitable for given business requirements. They will also explore each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances. The student will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. Introducing Data Platform Modernization Understand Data Platform Modernization Understanding the stages of migration Data Migration Paths Choose the right tools for Data Migration Discover the Database Migration Guide Build your data estate inventory using Map Toolkit Identify Migration candidates using Data Migration Assistant Evaluate a Data workload using Database Experimentation Assistant Data Migration using Azure Database Migration Service Migrate non-SQL Server workloads to Azure using SQL Migration Assistant Migrating SQL Workloads to Azure Virtual Machines Considerations of SQL Server to Azure VM Migrations SQL Workloads to Azure VM Migration Options Implementing High Availability and Disaster Recovery Scenarios Migrate SQL Workloads to Azure SQL Databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL DB offline Migrate SQL Server to Azure SQL DB online Load and Move data to Azure SQL Database Migrate SQL Workloads to Azure SQL Database Managed Instance Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed instance Load and Move data to SQL Database Managed instance Application Configuration and Optimization

Duration 0.5 Days 3 CPD hours This course is intended for This course is intended for: Line of Business (LoB) owners, IT leaders, and executives Overview In this course, you will learn to: Explain the role of information technology (IT) in an organization for business transformation Explain the customer value proposition for using the cloud across industries Define key characteristics of cloud computing Explain the cloud business model Identify key security practices of cloud computing Frame the cloud business value using the Cloud Value Framework In this course, you will learn the fundamental concepts of cloud computing and how a cloud strategy can help companies meet business objectives. It explores the advantages and possibilities of cloud computing. It also introduces addresses concepts such as security and compliance to help facilitate better discussions with line of business (LOB) professionals, information technology (IT) LoB, IT leaders, and executives. Module 1: Course Introduction Course Introduction Module 2: Information Technology for Business Transformation Role of IT in an organization for business transformation Brief history of IT Legacy approach to IT What drives customers to move from traditional infrastructure to the cloud Module 3: Cloud Computing Define cloud computing Key characteristics of cloud technology The cloud business model Key security practices within the cloud Module 4: Business Value of the Cloud The customer value proposition Identify who is using cloud computing Industry trends Customer examples Module 5: The Cloud Value Framework Introduction to the Cloud Value Framework Cost Savings Staff Productivity Operational Resilience Business Agility Module 6: Business Value Activity Business Value Activity Additional course details: Nexus Humans AWS Cloud Essentials for Business Leaders 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 AWS Cloud Essentials for Business Leaders 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.

Are you an EDI Officer, HR Specialist, Leader or Manager? Or the nominated EDI champion for your team? Maybe you've been given the EDI portfolio on behalf of your Board or department? Or if you're aiming to make a difference via your diverse staff network or union, all change-makers are welcome!

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Solutions architects Developers Cost-optimization leads System administrators Overview In this course, you will learn to: Explain the cost of core AWS services Determine and predict costs associated with current and future cloud workloads Use strategies and best practices to reduce AWS costs Use AWS tools to manage, monitor, alert, and optimize your AWS spend Apply strategies to monitor service costs and usage Implement governance standards, including resource tagging, account structure, provisioning,permissions, and access This course is for individuals who seek an understanding of how to manage, optimize, and predict costs as you run workloads on AWS. You learn how to implement architectural best practices, explore cost optimization strategies, and design patterns to help you architect cost-efficient solutions on AWS. Module 0: Couse Overview Course introduction Module 1: Introduction to Cloud Financial Management Introduction to Cloud Financial Management Four pillars of Cloud Financial Management Module 2: Resource Tagging Tagging resources Hands-On Lab: Cost optimization: Control Resource Consumption Using Tagging and AWS Config Module 3: Pricing and Cost Fundamentals of pricing AWS Free Tier Volume discounts Savings plans and Reserved Instances Demonstration: AWS Pricing Calculator Module 4: AWS Billing, Reporting, and Monitoring Understanding AWS invoices Reporting and planning AWS Cost Explorer AWS Budgets Demonstration: AWS Billing Console Demonstration: AWS Cost Explorer Demonstration: Trusted Advisor Hands-On Lab: Cost optimization: Deploy Ephemeral Environments Using Amazon EC2 Auto Scaling Module 5: Architecting for Cost: Compute Evolution of compute efficiency Amazon EC2 right-sizing Purchasing options Architect for Amazon EC2 Spot Instance Impact of software licensing Demonstration: Compute Optimizer Demonstration: Spot Instance Advisor Hands-On Lab: Cost optimization: Right Size Amazon EC2 Instances Using Amazon CloudWatch Metrics Module 6: Architecting for Cost: Networking Data transfer costs Understand data costs for different services How to triage network costs Hands-On Lab: Cost optimization: Reduce Data Transfer Costs Using Amazon CloudFront and Endpoints Module 7: Architecting for Cost: Storage Amazon EBS cost, pricing, and best practices Amazon S3 cost, pricing, and best practices Amazon EFS cost, pricing, and best practices Hands-On Lab: Cost optimization: Reduce Storage Costs Using Amazon S3 Lifecycle Management Module 8: Architecting for Cost: Databases Amazon RDS cost, pricing, and best practices Amazon Aurora cost, pricing, and best practices Amazon DynamoDB cost, pricing, and best practices Amazon ElastiCache cost, pricing, and best practices Amazon Redshift cost, pricing, and best practices Module 9: Cost Governance Setting up AWS Organizations AWS Systems Manager Hands-On Lab: Cost optimization: Reduce Compute Costs Using AWS Instance Scheduler Module 10: Course Summary Course review

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level course, designed for anyone wanting to learn Linux. Attendees should be comfortable working with computers and the command line, but no other specific skills are required to attend. Overview This skills-focused course is about 50% lab to lecture ratio, combining expert instructor-led discussions with practical hands-on labs that emphasize current techniques, best practices and standards. Working in a hands-on lab environment, guided by our expert practitioner, attendees will explore The Design of Linux Basic Operations File System Basics Wildcards File and Directory Permissions Working with files Executing Programs Using find Filters and other useful commands The vi editor Customizing the user environment Networking/Communications Backups and archiving This hands-on course provides you with an essentials-level foundation in core skills for using any version of Linux. This course focuses on essential skills that ordinary users might use daily when working with Linux. The Design of Linux A brief history of Linux The Linux design philosophy Linux architecture Basic Operations Logging in and out The general form of a Linux command Common commands Using man pages Essential commands File System Basics The Linux directory structure Standard directories Relative and absolute pathnames Legal file names Navigating the filesystem Wildcards Matching one character Matching many characters Shortcuts Wildcard gotchas Wildcards and ls File and Directory Permissions Viewing permissions File permissions Directory permissions Setting defaults Changing permissions Keeping data secure Working with files Viewing contents Identifying file contents Copying and moving Deleting Using symbolic links Executing Programs Redirecting STDOUT Redirecting STDERR Redirecting STDIN Creating pipelines Processes attributes Listing processes Killing processes Foreground & background processes Using find Syntax Finding by name, type, or size Combining tests Finding by size, owner, or timestamps Using xargs with find Other find options Filters and other useful commands What is a filter? cat: a generic filter head and tail grep sort wc other interesting filters The vi editor Why vi? Basic vi operations: navigating, adding, deleting Advanced operations: buffer management, search and replace, configuration options Customizing the user environment About shells Shell startup files Shell variables Search path Aliases Simple shell scripts Networking/Communications Reading and sending mail Remote login Remote file transfer Other network utilities (ping, finger, etc) Backups and archiving Checking space used or available Creating tar archives Viewing and extracting files from archives Compression utilities Working with windows

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 4 Days 24 CPD hours This course is intended for This course is the first in a series of two courses designed for programmers who are new to RPG IV. Basic programming experience is required. The student should have attended at least an introductory course to programming such as one of those available at technical colleges. The student is not taught the concepts of programming. Experienced programmers who are new to the Power System with IBM i should also attend this course. Examples of other programming languages are BASIC, COBOL, or RPG II. This course focuses entirely on the features of the RPG IV Version 7 compiler and the techniques that this compiler provides. Features of V7 are discussed. Previous techniques and the maintenance of programs that are written using legacy techniques, such as fixed format calculations, are not covered in the classroom. Some additional material and the bibliography will assist the new RPG IV programmer in the maintenance of legacy applications. Overview Write RPG IV version 7.1 programs to produce reportsWrite simple RPG IV version 7.1 inquiry programs that interact with displaysReview compilation listing, find and correct compilation errorsMaintain existing applications written in the RPG IV Version 7.1 languageUse many popular RPG IV built-in functions This course is a comprehensive exposure to the basic features and functions of RPG IV for Version 7. Course Outline RPG IV introduction Coding specifications for RPG IV Data representation and definition Manipulating data in calculations Using printer and display files in an RPG IV program Structured programming, error handling, subprocedures, and subroutines Using arrays, data structures, and data areas Accessing the DB2 database using RPG IV What's next? Additional course details: Nexus Humans AS06 IBM RPG IV Programming Fundamentals Workshop for IBM i 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 AS06 IBM RPG IV Programming Fundamentals Workshop for IBM i 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 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 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client