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Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

Duration 5 Days 30 CPD hours This course is intended for IT professionals across a broad range of disciplines who need to perform essential Linux administration tasks including installation, establishing network connectivity, managing physical storage, and basic security administration. This course relates to Red Hat Enterprise Linux 7 and is designed for IT pros without previous Linux admin experience. The course focuses on providing students with Linux admin 'survival skills' by focusing on core admin tasks. Access the command line Log in to a Linux system and run simple commands using the shell. Manage files from the command line Copy, move, create, delete, and organize files from the bash shell prompt. Getting help in Red Hat Enterprise Linux Resolve problems by using online help systems and Red Hat support utilities. Create, view, and edit text files Create, view, and edit text files from command output or in an editor Manage local Linux users and groups Manage local Linux users and groups, and administer local password policies. Control access to files with Linux file system permissions Set Linux file system permissions on files and interpret the security effects of different permission settings. Monitor and manage Linux processes Obtain information about the system, and control processes running on it. Control services and daemons Control and monitor network services and system daemons using systemd. Configure and secure OpenSSH service Access and provide access to the command line on remote systems securely using OpenSSH. Analyze and store logs Locate and accurately interpret relevant system log files for troubleshooting purposes. Manage Red Hat Enterprise Linux networking Configure basic IPv4 networking on Red Hat Enterprise Linux systems. Archive and copy files between systems Archive files and copy them from one system to another. Install and update software packages Download, install, update, and manage software packages from Red Hat and yum package repositories. Access Linux file systems Access and inspect existing file systems on a Red Hat Enterprise Linux system. Use virtualized systems Create and use Red Hat Enterprise Linux virtual machines with KVM and libvirt.

Duration 1 Days 6 CPD hours This course is intended for Individuals taking this course are business professionals seeking to develop or increase their emotional intelligence. Overview In this course, you will explore the concept of emotional intelligence. You will: Identify the components of emotional intelligence and recognize how emotional intelligence benefits organizations. Assess and develop your personal emotional intelligence competencies. Assess and develop your social emotional intelligence competencies. Practice emotional intelligence in common workplace scenarios. It was once believed that intelligence was the metric that would determine a person's success in the workplace. Intelligence matters because it contributes to your ability to do your job. But intelligence is not the best indicator of whether or not you'll succeed. Your ability to understand and manage your own emotions, and get along well with others, has at least as much impact on your performance and effectiveness as intelligence. In this course, you'll explore strategies to increase your awareness of your emotions, develop your ability to manage your emotions, and improve your social skills. Recognizing the Benefits of Emotional Intelligence Define Emotional Intelligence Recognize EQ's Impact on Work Experience Increasing Your Personal Emotional Intelligence in the Workplace Develop Your Level of Self-Awareness Develop Your Self-Regulation Skills Develop Your Motivation Increasing Your Social Emotional Intelligence in the Workplace Develop Your Empathy Develop Your Social Skills Practicing Emotional Intelligence in the Workplace Practice Emotionally Intelligent Leadership Build an Emotionally Intelligent Team Manage Change Manage Conflict Coach for Performance Additional course details: Nexus Humans Emotional Intelligence for Business Professionals (Second Edition) 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 Emotional Intelligence for Business Professionals (Second Edition) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: DevOps engineers DevOps architects Operations engineers System administrators Developers Overview In this course, you will learn to: Use DevOps best practices to develop, deliver, and maintain applications and services at high velocity on AWS List the advantages, roles and responsibilities of small autonomous DevOps teams Design and implement an infrastructure on AWS that supports DevOps development projects Leverage AWS Cloud9 to write, run and debug your code Deploy various environments with AWS CloudFormation Host secure, highly scalable, and private Git repositories with AWS CodeCommit Integrate Git repositories into CI/CD pipelines Automate build, test, and packaging code with AWS CodeBuild Securely store and leverage Docker images and integrate them into your CI/CD pipelines Build CI/CD pipelines to deploy applications on Amazon EC2, serverless applications, and container-based applications Implement common deployment strategies such as 'all at once,' 'rolling,' and 'blue/green' Integrate testing and security into CI/CD pipelines Monitor applications and environments using AWS tools and technologies DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization?s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included. Module 0: Course overview Course objective Suggested prerequisites Course overview breakdown Module 1: Introduction to DevOps What is DevOps? The Amazon journey to DevOps Foundations for DevOps Module 2: Infrastructure automation Introduction to Infrastructure Automation Diving into the AWS CloudFormation template Modifying an AWS CloudFormation template Demonstration: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection Module 3: AWS toolkits Configuring the AWS CLI AWS Software Development Kits (AWS SDKs) AWS SAM CLI AWS Cloud Development Kit (AWS CDK) AWS Cloud9 Demonstration: AWS CLI and AWS CDK Hands-on lab: Using AWS CloudFormation to provision and manage a basic infrastructure Module 4: Continuous integration and continuous delivery (CI/CD) with development tools CI/CD Pipeline and Dev Tools Demonstration: CI/CD pipeline displaying some actions from AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline Hands-on lab: Deploying an application to an EC2 fleet using AWS CodeDeploy AWS CodePipeline Demonstration: AWS integration with Jenkins Hands-on lab: Automating code deployments using AWS CodePipeline Module 5: Introduction to Microservices Introduction to Microservices Module 6: DevOps and containers Deploying applications with Docker Amazon Elastic Container Service and AWS Fargate Amazon Elastic Container Registry and Amazon Elastic Kubernetes service Demonstration: CI/CD pipeline deployment in a containerized application Module 7: DevOps and serverless computing AWS Lambda and AWS Fargate AWS Serverless Application Repository and AWS SAM AWS Step Functions Demonstration: AWS Lambda and characteristics Demonstration: AWS SAM quick start in AWS Cloud9 Hands-on lab: Deploying a serverless application using AWS Serverless Application Model (AWS SAM) and a CI/CD Pipeline Module 8: Deployment strategies Continuous Deployment Deployments with AWS Services Module 9: Automated testing Introduction to testing Tests: Unit, integration, fault tolerance, load, and synthetic Product and service integrations Module 10: Security automation Introduction to DevSecOps Security of the Pipeline Security in the Pipeline Threat Detection Tools Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector Module 11: Configuration management Introduction to the configuration management process AWS services and tooling for configuration management Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS) Module 12: Observability Introduction to observability AWS tools to assist with observability Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations Module 13: Reference architecture (Optional module) Reference architectures Module 14: Course summary Components of DevOps practice CI/CD pipeline review AWS Certification

Duration 0.25 Days 1.5 CPD hours This course is intended for This course is intended for individuals who want to learn how to stay safe online. Overview Upon successful completion of this course, students will be able to understand how to avoid social engineering and stay safe online. In this course, students will learn how to use the internet safely, and learn traps to avoid. The need for security Compliance Recognize social engineering and other attacks Secure Devices Passwords Identify viruses and malware Use the Internet safely Browsing the web Email Social media Cloud services Additional course details: Nexus Humans CyberSAFE: Staying Safe in a Digital World 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 CyberSAFE: Staying Safe in a Digital World 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 The primary audiences for the course are as follows: Cisco customers ? Contact Center Management, Contact Center Supervisors and Customer technical personnel Cisco technology partners Cisco employees Overview Upon completing this course, the learner will be able to meet these overall objectives: Provide a comprehensive overview of Cisco Unified Intelligence Center Describe reporting concepts and capabilities and features of Cisco Unified Intelligence Center reports Provide a detailed description and labs of how to modify reports from normal data sources (Cisco Unified CCE and Cisco Unified CVP) by customizing reports using various methods. (i.e. creating thresholds, show/hide columns, charts and more) The Cisco Unified Intelligence Center 11.6 for End Users (CUIC11.6EU v1.1) course is a two-day instructor-led training (ILT) course. Cisco Unified Intelligence Center is a comprehensive, end-to-end reporting solution, designed to make the task of creating and modifying reports easier on the customer and, at the same time, to present a consistent user interface and a common tool to access varied data across multiple Cisco product families. Cisco Unified Intelligence Center Overview Introducing Cisco Unified Intelligence Center What Contact Center products use CUIC for reporting Cisco Unified Intelligence Center Administration and Security The End User and CUIC Security Running and Modifying CUIC Reports Running Cisco Unified Intelligence Center Reports Using Permalinks Help Dashboards Modifying a CUIC Stock Report Cisco Unified Intelligence Center Dashboards Understanding Cisco Unified CCE Key Concepts Creating a New Cisco Unified Intelligence Center Report

Duration 2 Days 12 CPD hours This course is intended for #NAME? Overview The learning objectives for CDA include a practical understanding of: Goals, history, terminology, and pipeline The importance, practices, and transformation of a DevOps collaborative culture Design practices, such as modular design and microservices Continuous Integration (Cl), such as version control, builds, and remediation Tenets and best practices of Continuous Testing (CT) Continuous Delivery and Deployment (CD): packaging, containers, and release Continuous Monitoring (CM): monitoring and analysis infrastructure, process, and apps Infrastructure and tools: frameworks, tools, and infrastructure as code Security Assurance: DevSecOps The opportunity to hear and share real-life scenarios This course is designed for participants who are engaged in the design, implementation, and management of DevOps deployment pipelines and toolchains that support Continuous Integration, Continuous Delivery, Continuous Testing and potentially Continuous Deployment. The course highlights underpinning processes, metrics, APls and cultural considerations with Continuous Delivery. Key benefits of Continuous Delivery will be covered including increased velocity to assist organizations to respond to market changes rapidly, thus being able to outmaneuver competition, reduce risk and lower costs while releasing higher quality solutions. Increased productivity and employee morale by having more activities performed by pipelines instead of humans so teams can focus on vision while pipelines do the execution.This course prepares you for the Continuous Delivery Ecosystem Foundation(CDEF) certification. Course Introduction Course goals Course agenda CDA Concepts Continuous delivery (CD) definition Architecting for continuous delivery Continuous delivery and DevOps Relationships between CD, Waterfall, Agile, ITIL, and DevOps Benefits of continuous delivery CDA Culture Importance of culture to the CD Architect What a CD Architect can do about culture How to maintain culture Assignment: DevOps culture and practices to create flow Design Practices for Continuous Delivery Why design is important to continuous delivery CD Architect?s role in design Key design principles CD best practices Microservices and containers Continuous Integration Continuous integration (CI) defined CD Architect?s role in CI Importance of CI Benefits of CI CI best practices Assignment: Optimizing CI workflows Continuous Testing Continuous testing (CT) defined Importance of CT Benefits of CT CD Architect?s role in CT Five tenets of CT CT best practices Assignment: Handling environment inconsistencies Continuous Delivery and Deployment Continuous delivery defined Continuous deployment defined Benefits of continuous delivery and deployment CD Architect?s role in continuous delivery and deployment Continuous delivery and deployment best practices Assignment: Distinguishing continuous delivery and deployment Continuous Monitoring Continuous monitoring defined Importance of continuous monitoring CD Architect?s role in continuous monitoring Continuous monitoring best practices Assignment: Monitoring build progress Infrastructure and Tools Importance of infrastructure and tools CD Architect?s role in infrastructure and tools Building a DevOps toolchain Infrastructure/tools best practices Assignment: identifying common infrastructure/tool components Security Assurance Importance of security assurance DevSecOps and Rugged DevOps defined CD Architect?s role in security Security best practices Assignment: Applying security practices Capstone exercise Identifying toolchain and workflow improvements Summary Additional Sources of Information Exam Preparations Exam requirements Sample exam review

Duration 4 Days 24 CPD hours This course is intended for This course is appropriate for developers and administrators who intend to use HBase. Overview Skills learned on the course include:The use cases and usage occasions for HBase, Hadoop, and RDBMSUsing the HBase shell to directly manipulate HBase tablesDesigning optimal HBase schemas for efficient data storage and recoveryHow to connect to HBase using the Java API, configure the HBase cluster, and administer an HBase clusterBest practices for identifying and resolving performance bottlenecks Cloudera University?s four-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Introduction to Hadoop & HBase What Is Big Data? Introducing Hadoop Hadoop Components What Is HBase? Why Use HBase? Strengths of HBase HBase in Production Weaknesses of HBase HBase Tables HBase Concepts HBase Table Fundamentals Thinking About Table Design The HBase Shell Creating Tables with the HBase Shell Working with Tables Working with Table Data HBase Architecture Fundamentals HBase Regions HBase Cluster Architecture HBase and HDFS Data Locality HBase Schema Design General Design Considerations Application-Centric Design Designing HBase Row Keys Other HBase Table Features Basic Data Access with the HBase API Options to Access HBase Data Creating and Deleting HBase Tables Retrieving Data with Get Retrieving Data with Scan Inserting and Updating Data Deleting Data More Advanced HBase API Features Filtering Scans Best Practices HBase Coprocessors HBase on the Cluster How HBase Uses HDFS Compactions and Splits HBase Reads & Writes How HBase Writes Data How HBase Reads Data Block Caches for Reading HBase Performance Tuning Column Family Considerations Schema Design Considerations Configuring for Caching Dealing with Time Series and Sequential Data Pre-Splitting Regions HBase Administration and Cluster Management HBase Daemons ZooKeeper Considerations HBase High Availability Using the HBase Balancer Fixing Tables with hbck HBase Security HBase Replication & Backup HBase Replication HBase Backup MapReduce and HBase Clusters Using Hive & Impala with HBase Using Hive and Impala with HBase Appendix A: Accessing Data with Python and Thrift Thrift Usage Working with Tables Getting and Putting Data Scanning Data Deleting Data Counters Filters Appendix B: OpenTSDB

Duration 1 Days 6 CPD hours This course is intended for Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

Duration 4 Days 24 CPD hours This course is intended for Data center architects Cloud infrastructure architects Network engineers System administrators Storage administrators Engineers requiring advanced configuration skills Cisco integrators and partners Overview After taking this course, you should understand: Data center challenges and cloud solutions Cisco UCS Director architecture Cisco UCS Director setup and configuration Cisco ACI Multitenancy in FlexPod Cisco ACI infrastructure Resource groups and service offerings Tenant onboarding Self-service provisioning Application containers The Designing and Deploying Cisco UCS Director with ACI (UCSDACI) v6.6 course shows you how to use Cisco UCS© Director software to manage physical and virtual infrastructure elements, including Cisco Application Centric Infrastructure (Cisco ACI?). You will learn to use orchestration and automation functions of Cisco UCS Director to effectively manage infrastructure and automate IT processes. The course offers hands-on experience installing and configuring Cisco UCS Director software. You will also learn about features such as bare-metal provisioning; compute, network, and storage management; orchestration, including Application Policy Infrastructure Controller (APIC); Cisco UCS Director custom tasks, and more. Introducing Cisco UCS Director Understanding Data Center Challenges Understanding the Benefits of Cisco UCS Director Understanding Cisco UCS Director Components Explaining Cisco UCS Director Architecture Explaining Bare-Metal Agent Introducing Cisco Application Centric Infrastructure Understanding Cisco ACI Overview Understanding Cisco ACI Terms and Constructs Understanding Cisco UCS Director Infrastructure Management Understanding Cisco UCS Director Deployment Introducing Role-Based Access Control Explaining User Groups/Roles/Users Introducing Orchestration Understanding Orchestration Introducing Cisco UCS Director ACI Explaining Cisco UCS Director with ACI So Understanding Multitenancy with Cisco UCS Director ACI Explaining Multitenancy with Cisco UCS Director ACI Understanding Resource Groups and Service Offerings Introducing Advanced Tenant Onboarding Onboarding a Tenant Tagging Resources Introducing Application Containers Understanding Application Profiles Understanding Service Container Catalog Understanding Deployment Through Self-Service Portal Understanding Self-Service Provisioning Portal Understanding Service Request Understanding Virtual Data Center Understanding Policies Understanding vDC and Groups Use Case Additional course details: Nexus Humans CiscoDesigning and Deploying Cisco UCS Director with ACI (UCSDACI) v6.6 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 CiscoDesigning and Deploying Cisco UCS Director with ACI (UCSDACI) v6.6 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.