2391 Architect courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for System installers System integrators System administrators Network administrators Solutions designers Overview After taking this course, you should be able to: Describe the Cisco SD-WAN solution and how modes of operation differ in traditional WAN versus SD-WAN Describe options for Cisco SD-WAN cloud and on-premises deployment Explain how to deploy WAN Edge devices Review the Zero-Touch Provisioning (ZTP) process and examine technical specifics for on-premises deployment Review the device configuration template and describe new features of device configuration templates Describe options for providing scalability, high availability, and redundancy Explain how dynamic routing protocols are deployed in an SD-WAN environment, on the service side and transport side Describe Cisco SD-WAN policy concepts, which includes how policies are defined, attached, distributed, and applied Define and implement advanced control policies, such as policies for custom topologies and service insertion Identify and implement advanced data policies, such as policies for traffic engineering and QoS Define and implement an Application-Aware Routing (AAR) policy Implement Direct Internet Access (DIA) and Cisco SD-WAN Cloud OnRamp options Describe Cisco SD-WAN security components and integration Describe how to design pure and hybrid Cisco SD-WAN solutions, as well as how to perform a migration to Cisco SD-WAN Describe Cisco SD-WAN Day-2 operations, such as monitoring, reporting, logging, troubleshooting, and upgrading Describe Cisco SD-WAN support for multicast The Implementing Cisco SD-WAN Solutions (ENSDWI) v2.0 course gives you training about how to design, deploy, configure, and manage your Cisco© Software-Defined WAN (SD-WAN) solution in a large-scale live network, including how to migrate from legacy WAN to SD-WAN. You will learn best practices for configuring routing protocols in the data center and the branch, as well as how to implement advanced control, data, and application-aware policies. The course also covers SD-WAN deployment and migration options, placement of controllers, how to deploy WAN Edge devices, and how to configure Direct Internet Access (DIA) breakout. The course looks at the different Cisco SD-WAN security options available, such as application-aware enterprise firewall, Intrusion Prevention System (IPS), URL filtering, Cisco Advanced Malware Protection (AMP), Secure Sockets Layer/Transport Layer Security (SSL/TLS) proxy, and Cisco Umbrella© Secure Internet Gateway (SIG). This course helps you prepare to take the Implementing Cisco SD-WAN Solutions (300-415 ENSDWI) exam which is part of the CCNP© Enterprise certification. You will also earn 32 Continuing Education (CE) credits toward recertification. Course outline Examining the Cisco SD WAN Architecture Examining Cisco SD-WAN Deployment Options Deploying WAN Edge Devices Onboarding WAN Edge Devices with ZTP and PnP Using Device Configuration Templates Exploring Redundancy, High Availability, and Scalability Enabling Service-Side and Transport-Side Routing Understanding Cisco SD-WAN Policy Configuration Basics Defining Advanced Control Policies Implementing AAR Examining Direct Internet Access and Cloud Deployment Options Exploring Cisco SD-WAN Security Designing and Migrating to Cisco SD-WAN Performing Cisco SD-WAN Network Management and Troubleshooting Examining Cisco SD-WAN Multicast Support Lab outline Deploy Cisco SD-WAN Controllers Add a WAN Edge Router Using ZTP Deploy Cisco SD-WAN Device Using Configuration Templates Configure Cisco SD-WAN Controller Affinity Implement Service Side Routing Protocols Implement Transport Location (TLOC) Extensions Implement Control Policies Implement Data Policies Implement Application-Aware Routing Implement Branch and Regional Internet Breakouts Migrate Branch Sites Perform Cisco SD-WAN Software Upgrade Additional course details: Nexus Humans Cisco Implementing Cisco SD-WAN Solutions (ENSDWI) v2.0 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 Cisco Implementing Cisco SD-WAN Solutions (ENSDWI) v2.0 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 Experienced system administrators or network administrators Network professionals who have experience working with VMware NSX Advanced Load Balancer (Avi) and are responsible for troubleshooting and operating Application Delivery Controllers solutions Overview By the end of the course, you should be able to meet the following objectives: Become familiar with NSX Advanced Load Balancer (Avi) troubleshooting tools and steps to solve the problems. Establish and apply a structured troubleshooting approach and methodology Understand built-in mechanisms available for NSX Advanced Load Balancer (Avi) monitoring Identify, analyze, and troubleshoot problems related to the NSX Advanced Load Balancer infrastructure, including control and data plane components Identify, analyze, and troubleshoot problems related to application components such as Virtual Services, Pools, and related components This 3-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competence in operating and troubleshooting the VMware NSX© Advanced Load Balancer? (Avi) solutions. In this course, you are introduced to several operational, management, and troubleshooting tools. You will be presented with various types of technical problems, which you will identify, analyze, and solve through a systematic process. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and functions Events and Alerts Describe NSX Advanced Load Balancer Events Describe and configure NSX Advanced Load Balancer Alerts Describe NSX Advanced Load Balancer monitoring capabilities leveraging SNMP, Syslog, and email Introduction to NSX Advanced Load Balancer Troubleshooting Explain NSX Advanced Load Balancer troubleshooting concepts Describe and leverage Virtual Service Traffic Logs Describe and leverage Virtual Service Security Insights Understand and utilize Health Score concepts Explain and leverage application metrics and analytics Explain and leverage packet capture and CLI utilities for application troubleshooting Leverage UI, CLI, and useful log files to perform control plane troubleshooting Infrastructure Troubleshooting Describe and perform general VMware Cloud Connector troubleshooting Describe and analyze VMware Cloud Connector state Leverage case studies to troubleshoot VMware Cloud Connector Describe and troubleshoot NSX-T Cloud Connector integration Leverage case studies to troubleshoot NSX-T Cloud Connector Describe and troubleshoot Linux Server Cloud Connector integration Describe and troubleshoot OpenStack Cloud Connector integration Leverage case studies to troubleshoot OpenStack Cloud Connector Describe and troubleshoot AWS and Azure Cloud Connector integrations Troubleshooting NSX Advanced Load Balancer Service Engines and Advanced Troubleshooting Explain general Service Engine infrastructure Explain and leverage analytics, health score, and metrics for Service Engine troubleshooting Explain and leverage Events and Alerts for Service Engine troubleshooting Leverage CLI for accessing Service Engine Analyze Service Engine logs offline with Tech Support utility and collecting core dumps Leverage CLI and useful log files for Service Engine Data Plane troubleshooting Leverage CLI to capture packets for advanced datapath analysis Monitoring NSX Advanced Load Balancer Explain and configure SNMP-based monitoring Explain and configure REST API-based monitoring Describe and leverage 3rd-party integration with monitoring tools like Splunk Leverage 3rd-party REST API monitoring extensions like Prometheus Describe and leverage VMware integrations like VMware vRealize© Network Insight? for monitoring Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware NSX Advanced Load Balancer: Troubleshooting and Operations [V20.x] 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 VMware NSX Advanced Load Balancer: Troubleshooting and Operations [V20.x] 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 The primary audience for this course is as follows - IT Staff and Managers - Network and systems personnel and engineers - Small to mid-sized organizations that require fundamental knowledge on networking terms/concepts and configuration guidance for Meraki equipment This also includes organizations looking to implement remote sites, provide a guest wireless solution, and collect user analytics Overview Upon completing this course, the student will be able to meet these objectives: Students will be able to Deploy and Manage a Meraki Network using the Meraki Dashboard - Deploy, Manage, Monitor and Troubleshoot Meraki MS Switches - Deploy, Manage, Monitor and Troubleshoot Meraki MR Wireless Access Points - Deploy, Manage, Monitor and Troubleshoot Meraki MX Firewall Appliances - Deploy, Manage, Monitor and Troubleshoot Meraki MV IP Video Cameras - Deploy, Manage, Monitor and Troubleshoot Meraki MC Phones - Deploy, Manage, Monitor and Troubleshoot Meraki Systems Manager - Deploy, Manage, Monitor and Troubleshoot Meraki SDWAN This course familiarizes individuals with networking concepts and demonstrates how to effectively use Meraki products to build a comprehensive network Cisco/Meraki Product Line Introduction MS - Switching MR - Wireless LAN MX - Security MV ? Camera MC - Voice SD-WAN Cisco/Meraki Cloud Management Introduction to cloud management The dashboard and navigation Organizations & Networks ? what is the difference and how to use them System-wide parameters (organization parameters) Cisco/Meraki Dashboard Administration Creating and implementing maps Summary Report and Auto Generation Reports Adding administrators and tweaking security levels Using Tags and Configuring Alerting (SNMP, email) Adding admins, configuring reports, and alerts Firmware Management Configuring Authentication Lab 1 Lab 2 Configuring external authentication Configuring Group Policies Device Replacement Location Analytics Other advanced analytics Cisco/Meraki Switching Review switching basics Review Meraki L2 Switch Models Configuring Meraki Switches Troubleshooting / Diagnostics Lab 3 Cisco/Meraki Routing Review routing basic (IP Addresses, Networks and Masks, OSPF, etc.) Review Meraki L3 switch Models Configuring Meraki Switches for Routing Lab 4 Cisco/Meraki Wireless Review Wireless Basics Meraki Wireless Product Review Performing a Site Survey Configuring Access Points Lab 5 Cisco/Meraki Firewalls/Security Review firewall basics Meraki Firewall Model Review Configuring a Meraki Firewall Lab 6 IP Cameras MV21 vs MV71 Installing Cameras Adding Cameras to the Dashboard Managing MV Cameras Troubleshooting Cameras Lab 7 Meraki Communications QOS Voice Security Deploying Meraki MC74 Phones Deploying Cisco IP Phones to CUCM Deploying Voice Features End User Lab 8 Meraki Systems Manager Controlling Wireless Device Policies Enrolling Devices Apps Profiles Tags Security Policies Geofencing Policies Lab 9 Meraki SDWAN What is SD-WAN? Concentrator Mode VPN Topology Split Tunnel Full Tunnel Hub and Spoke VPN Mesh Datacenter Redundancy (DC-DC Failover) Warm Spare (High Availability) for VPN concentrators Connection Monitor Dual-Active VPN uplinks Policy-based Routing Dynamic Path Selection SD-WAN Objectives Example Topology High Level Traffic Flow SD-WAN Technologies Deploying a one-armed concentrator Dashboard Configuration Other Datacenter Configuration MX IP Assignment Upstream Considerations Datacenter Redundancy (DC-DC Failover) High-level architecture Failover Times Datacenter Deployment Branch Deployment Lab 10 Meraki Support Getting support for Meraki Finding the Right Documentation Posting in the Community Troubleshooting Meraki Connectivity Issues Resetting Devices. Additional course details: Nexus Humans Implementing and Configuring Meraki Technologies v1.0 (ICMT - CT) 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 Implementing and Configuring Meraki Technologies v1.0 (ICMT - CT) 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 Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 2 Days 12 CPD hours This course is intended for This program is designed for students who have attended successfully the IJOS and JRE courses (prior to April 1, 2017) or the IJOS course (since April 3, 2017) and are working toward JNCIA-JUNOS certification. Overview The objectives for this course follow the requirements for the current JNCIA-JUNOS. At the end of this course, the successful student will be able to: Identify the concepts and functionality of various fundamental elements of networking Identify the concepts, benefits and functionality of the core elements of the Junos OS Identify the concepts, operation and functionality of the Junos user interfaces Identify the main elements for configuring Junos devices Describe how to configure basic components of a Junos device Identify methods of monitoring and maintaining Junos devices Describe monitoring and maintenance procedures for a Junos device Identify basic routing concepts and functionality for Junos devices Describe how to configure and monitor basic routing elements for a Junos device Identify the concepts and functionality of routing policy and firewall filters on Junos devices Describe how to configure and monitor routing policies and firewall filters on a Junos device Apply knowledge of Junos operating system configuration, operations, and functionality to real-world scenarios This intense, two-day program is designed to prepare attendees who have previously taken the Introduction to the Junos Operating System (IJOS) course for taking the certification exam while simultaneously gaining insight into real-world applications Session 1: Practice Labs Guided practice labs to reintroduce the lab environment Session 2: Real-World Scenario Labs Labs that emulate real-world application of JNCIA-level knowledge, configurations, operations, and functionality. These labs will challenge students to complete scenario-based problems to accomplish specific network goals. Session 3: Networking Fundamentals Collision domains and broadcast domains Function of routers and switches Optical network fundamentals ? SONET/SDH, OTN Ethernet networks Layer 2 addressing, including address resolution IPv4 and IPv6 fundamentals Layer 3 / IP addressing, including subnet masks Subnetting and supernetting Decimal to binary conversion Longest match routing Connection-oriented vs. connectionless protocols Session 4: Junos OS Fundamentals Junos device portfolio ? product families, general functionality Software architecture Control and forwarding planes Routing Engine and Packet Forwarding Engine Protocol daemons Transit traffic processing Exception traffic Session 5: User Interfaces CLI functionality CLI modes CLI navigation CLI Help Filtering output Active vs. candidate configuration Reverting to previous configurations Modifying, managing, and saving configuration files Viewing, comparing, and loading configuration files J-Web ? core/common functionality Session 6: Junos Configuration Basics Initial configuration User accounts Login classes User authentication methods Interface types and properties Configuration groups Additional initial configuration elements ? NTP, SNMP, syslog, etc. Configuration archival Logging and tracing Rescue configuration Session 7: Operational Monitoring and Maintenance Show commands Monitor commands Interface statistics and errors Network tools ? ping, traceroute, telnet, SSH, etc. Real-time performance monitoring (RPM) Junos OS installation Software upgrades Powering on and shutting down Junos devices Root password recovery Session 8: Routing Fundamentals Packet forwarding concepts Routing tables Routing vs. forwarding tables Route preference Routing instances Static routing Advantages of / use cases for dynamic routing protocols Session 9: Routing Policy and Firewall Filters Default routing policies Import and export policies Routing policy flow Effect of policies on routes and routing tables Policy structure and terms Policy match criteria, match types, and actions Firewall filter concepts Firewall filter concepts Filter match criteria and actions Effect of filters on packets Unicast reverse-path-forwarding (RPF) Session 10: JNCIA-JUNOS Certification Exam The exam voucher is included in the price of the course DWWTC is a certified PearsonVUE Testing Center' Additional course details: Nexus Humans JNCIA Practicum and Exam Preparation 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 JNCIA Practicum and Exam Preparation 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 Server administrators Network engineers Systems engineers Consulting systems engineers Technical solutions architects Network administrators Storage administrators Network managers Cisco integrators and partners Overview After taking this course, you should be able to: Describe and implement Fibre Channel, zoning, and N-Port Virtualization (NPV) features on Cisco UCS Describe and implement Fibre Channel over Ethernet (FCoE) on Cisco UCS Describe Cisco UCS policies for service profiles Describe Cisco Adapter Fabric Extender (FEX) and Single Root I/O Virtualization Describe and implement Role-Based Access Control (RBAC) on Cisco UCS Describe and implement external authentication providers on Cisco UCS Manager Describe and implement key management on Cisco UCS Manager Describe Cisco UCS Director Describe and implement Cisco Intersight Describe the scripting options for Cisco UCS Manager Describe and implement monitoring on Cisco UCS Manager The Configuring Cisco Unified Computing System (DCCUCS) v1.0 shows you how to deploy, secure, operate, and maintain Cisco Unified Computing System? (Cisco UCS©) B-series blade servers, Cisco UCS C-Series, and S-Series rack servers for use in data centers. You will learn how to implement management and orchestration software for Cisco UCS. You will gain hands-on practice: configuring key features of Cisco UCS, Cisco UCS Director, and Cisco UCS Manager; implementing UCS management software including Cisco UCS Manager and Cisco Intersight?; and more. Implementing Cisco UCS Storage Area Network (SAN) SAN Introduction Cisco UCS Fabric Interconnect Fibre Channels modes Named VSANs Cisco UCS Fibre Channel and FCoE Storage Connectivity Describing Cisco UCS Policies for Service Profiles Storage Policies and Profiles Basic Input Output System (BIOS) Policies Boot Policy Intelligent Platform Management Interface (IPMI) Policies Scrub Policies Maintenance Policies Describing Cisco Adapter FEX and Single Root I/O Virtualization Cisco FEX Overview Cisco Adapter FEX Single Root I/O Virtualization Implementing RBAC on Cisco UCS RBAC in Cisco UCS Users, Roles, and Privileges Functions of Organizations and Locales Effective Rights of a User Implementing External Authentication Providers Options for External Authentication Providers Implementing Key Management on Cisco UCS Manager Public Key Infrastructure Implementing Cisco UCS Director Cisco UCS Director Overview Policies, Virtual Data Centers, and Catalogs Cisco UCS Director Virtualization Support Managing Compute with Cisco UCS Director Cisco UCS Manager Orchestration Self-Service Portal Reporting and Monitoring in Cisco UCS Director Implementing Cisco Intersight Cisco UCS Director Overview Important Features of Cisco Intersight Describing the Scripting Options for Cisco UCS Manager Cisco UCS Manager XML API Cisco UCS Management Information Tree Managed Object Browser Cisco UCS PowerTool Cisco UCS Python Software Development Kit (SDK) Implementing Key Management on Cisco UCS Manager Public Key Infrastructure Implementing Cisco Intersight Cisco Intersight Overview Important Features of Cisco Intersight Describing the Scripting Options for Cisco UCS Manager Cisco UCS Manager XML API Cisco UCS Management Information Tree Managed Object Browser Cisco UCS Manager PowerTool Cisco UCS Python SDK Implementing Monitoring on Cisco UCS Manager Logging Sources in Cisco UCS Manager Port Monitoring Capabilities of Cisco UCS Manager Simple Network Management Protocol (SNMP) Security Ramifications Cisco UCS Manager Call Home Feature Lab outline Configure Pod-Specific Device Aliases Configure Zoning Configure VSANs in Cisco UCS Manager Configure Unified Ports on Cisco UCS Fabric Interconnects Install and Boot VMware Elastic Sky X Integrated (ESXi) on Cisco UCS from the FCoE Logical Unit Number (LUN) via FCoE Configure RBAC Configure Cisco UCS Manager to Authenticate Users via Open Lightweight Directory Access Protocol (OpenLDAP) Configure a Trusted Point and Key Ring in Cisco UCS Manager Configure Cisco UCS with Cisco Intersight Configure Cisco UCS Manager Using Scripting Implement Syslog and Call Home Additional course details: Nexus Humans Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS) 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 Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS) 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 Experienced system administrators and system integrators responsible for designing and implementing vSphere with Kubernetes Overview By the end of the course, you should be able to meet the following objectives: Describe vSphere with Kubernetes and use cases in on-premises environments Deploy vSphere with Kubernetes Describe the VMware NSX networking requirements for vSphere with Kubernetes. Create and manage vSphere with Kubernetes namespaces Deploy and run container applications on vSphere with Kubernetes Deploy and configure VMware Harbor Describe the VMware Tanzu™ Kubernetes Grid™ service Deploy a Tanzu Kubernetes Grid cluster Deploy and run container applications on a Tanzu Kubernetes Grid cluster Describe the vSphere with Kubernetes lifecycle Use logs and CLI commands to monitor and troubleshoot vSphere with Kubernetes During this 3-day course, you focus on deploying and managing VMware vSphere© with Kubernetes. You learn about how vSphere with Kubernetes can be used to orchestrate the delivery of Kubernetes clusters and containerized applications in a VMware vSphere© environment. Course Introduction Introductions and course logistics Course objectives Introduction to Containers and Kubernetes Describe Virtual Machines and Containers Describe Container Hosts Describe Container Engines Describe Dockerfile Describe Container Images Describe Image Registry Describe the purpose and functionality of Kubernetes Describe Manifest YAML files Explain Pod YAML files Explain ReplicaSets Explain Services Explain Deployments Introduction to vSphere with Kubernetes Describe the purpose and functionality of vSphere with Kubernetes Explain the integration with VMware Tanzu? Mission Control? Describe the capabilities of vSphere with Kubernetes Describe the components of vSphere with Kubernetes Contrast vSphere with Kubernetes to traditional Kubernetes Describe the requirements for vSphere with Kubernetes Prepare a vSphere cluster for vSphere with Kubernetes Describe the NSX components required for vSphere with Kubernetes Describe the network topology of vSphere with Kubernetes Explain the networking requirements of vSphere with Kubernetes Compare NSX networking objects with Kubernetes networking objects vSphere with Kubernetes Core Services Explain the architecture of the vSphere with Kubernetes Core Services Describe the Container Service Describe the Volume Service Describe the Network Service Describe the Registry Service Describe the use cases of vSphere with Kubernetes Enable vSphere with Kubernetes Deploy VMware Harbor Registry vSphere with Kubernetes Namespaces Describe a vSphere with Kubernetes namespace Contrast a vSphere with Kubernetes namespace to a traditional Kubernetes namespace Describe Resource Quotas Explain Authentication and Authorization to vSphere with Kubernetes Explain the use cases of namespaces Create a namespace Describe kubectl Use kubectl to interact with vSphere with Kubernetes Describe using kubectl pod deployment Explain scaling a pod deployment Explain managing pod lifecycle Explain deleting pods Use kubectl to deploy a pod Use kubectl to scale a pod Use kubectl to switch between namespaces VMware Tanzu Kubernetes Grid service Explain Tanzu Kubernetes Grid service Describe the use cases for Tanzu Kubernetes Grid clusters Describe the integration with Tanzu Mission Control Explain the lifecycle of Tanzu Kubernetes Grid clusters Deploy Tanzu Kubernetes Grid cluster Deploy pods to a Tanzu Kubernetes Grid cluster Monitoring and Troubleshooting Describe the monitoring tools for vSphere with Kubernetes Describe the troubleshooting tools for vSphere with Kubernetes Explain cluster, node, and namespace health Explain usage and capacity monitoring Describe vCenter Server events Describe vSphere with Kubernetes events Gather support information vSphere with Kubernetes Lifecycle Describe the vSphere with Kubernetes lifecycle Describe the Tanzu Kubernetes Grid lifecycle Describe scaling a vSphere with Kubernetes cluster Update vSphere with Kubernetes Update Tanzu Kubernetes Grid clusters Remove vSphere with Kubernetes Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSphere with Tanzu: Deploy and Manage [V7] 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 VMware vSphere with Tanzu: Deploy and Manage [V7] 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 intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Duration 2 Days 12 CPD hours This course is intended for This introduction to Spring development course requires that incoming students possess solid Java programming skills and practical hands-on Java experience. This class is geared for experienced Java developers who are new to Spring, who wish to understand how and when to use Spring in Java and JEE applications. Overview Working in a hands-on learning environment, led by our expert practitioner, students will: Explain the issues associated with complex frameworks such as JEE and how Spring addresses those issues Understand the relationships between Spring and JEE, AOP, IOC and JDBC. Write applications that take advantage of the Spring container and the declarative nature of assembling simple components into applications. Understand how to configure the Spring Boot framework Understand and work on integrating persistence into a Spring application Explain Spring's support for transactions and caching Work with Spring Boot to facilitate Spring setup and configuration Apply Aspect Oriented Programming (AOP) to Spring applications Become familiar with the conditionally loading of bean definitions and Application Contexts Understand how to leverage the power of Spring Boot Use Spring Boot to create and work with JPA repositories Introduction to Spring Boot | Spring Boot Quick Start is a hands-on Spring training course geared for experienced Java developers who need to understand what the Spring Boot is in terms of today's systems and architectures, and how to use Spring in conjunction with other technologies and frameworks. This leading-edge course provides added coverage of Spring's Aspect-Oriented Programming and the use of Spring Boot. Students will gain hands-on experience working with Spring, using Maven for project and dependancy management, and, optionally, a test-driven approach (using JUnit) to the labs in the course. The Spring framework is an application framework that provides a lightweight container that supports the creation of simple-to-complex components in a non-invasive fashion. Spring's flexibility and transparency is congruent and supportive of incremental development and testing. The framework's structure supports the layering of functionality such as persistence, transactions, view-oriented frameworks, and enterprise systems and capabilities. This course targets Spring Boot 2 , which includes full support for Java SE 11 and Java EE 8. Spring supports the use of lambda expressions and method references in many of its APIs. The Spring Framework Understand the value of Spring Explore Dependency Injection (DI) and Inversion of Control (IoC) Introduce different ways of configuring collaborators Spring as an Object Factory Initializing the Spring IoC Container Configuring Spring Managed Beans Introduce Java-based configuration The @Configuration and @Bean annotations Define bean dependencies Bootstrapping Java Config Context Injection in Configuration classes Using context Profiles Conditionally loading beans and configurations Bean Life-Cycle Methods Defining Bean dependencies Introduce Spring annotations for defining dependencies Explore the @Autowired annotation Stereotype Annotations Qualifying injection points Lifecycle annotations Using properties in Java based configuration The @Value annotation Using the Candidate Components Index Introduction to Spring Boot Introduce the basics of Spring Boot Explain auto-configuration Introduce the Spring Initializr application Bootstrapping a Spring Boot application Working with Spring Boot Provide an overview of Spring Boot Introduce starter dependencies Introduce auto-configuration @Enable... annotations Conditional configuration Spring Boot Externalized Configuration Bootstrapping Spring Boot Introduction to Aspect Oriented Programming Aspect Oriented Programming Cross Cutting Concerns Spring AOP Spring AOP in a Nutshell @AspectJ support Spring AOP advice types AspectJ pointcut designators Spring Boot Actuator Understand Spring Boot Actuators Work with predefined Actuator endpoints Enabling Actuator endpoints Securing the Actuator Developing in Spring Boot Introduce Spring Boot Devtools Enable the ConditionEvaluationReport Debugging Spring Boot applications Thymeleaf Provide a quick overview of Thymeleaf Introduce Thymeleaf templates Create and run a Spring Thymeleaf MVC application Additional course details: Nexus Humans Spring Boot Quick Start | Core Spring, Spring AOP, Spring Boot 2.0 and More (TT3322) 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 Spring Boot Quick Start | Core Spring, Spring AOP, Spring Boot 2.0 and More (TT3322) 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.