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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 1 Days 6 CPD hours This course is intended for This course does not have any technical knowledge prerequisites for the learners, besides being proficient in using a computer and the Internet. IT and/or AI knowledge is a benefit but not a hard requirement. Given the rapid development of AI and the broad range of its applications in everyday life, it is crucial for anyone to attend this course to update their digital skills in an ever-changing world. It is expected that all learners have registered for a free account of OpenAI ChatGPT at https://chat.openai.com. Overview Discover how AI relates to other 4th industrial revolution technologies Learn about AI, ML, and associated cognitive services Overview of AI development frameworks, tools and services Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail The core aim of this ?AI for beginners? course is to introduce its audience to Artificial Intelligence (AI) and Machine Learning (ML) technologies and allow them to understand the practical applications of AI in their everyday personal and professional life. Moreover, the course aims to provide a handful of demos and hands-on exercises to allow the learners to familiarize themselves with usage scenarios of OpenAI ChatGPT and other Generative AI (GenAI) models. The content of this course has been created primarily by using the OpenAI ChatGPT model. AI theoretical concepts. Introduction to AI, ML, and associated cognitive services (Computer vision, Natural language processing, Speech analysis, Decision making). How AI relates to other 4th industrial revolution technologies (cloud computing, edge computing, internet of things, blockchain, metaverse, robotics, quantum computing). AI model classification by utilizing mind maps and the distinctive role of Gen AI models. Introduction to the OpenAI ChatGPT model and alternative generative AI models. Familiarization with the basics of the ChatGPT interface (https://chat.openai.com). Talking about Responsible AI: Security, privacy, compliance, copyright, legal challenges, and ethical implications. AI practical applications Overview of AI development frameworks, tools and services. AI aggregators review. Hand-picked AI tool demos: a.Workplace productivity and the case of Microsoft 365 Copilot. b.The content creation industry. Create text, code, images, audio and video with Gen AI. c.Redefining the education sector with AI-powered learning. Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail: a.Prompting and plugin demos. b.Code interpreter demos. Closing words. Discussion with an AI model on the future of AI. Additional course details: Nexus Humans AI for beginners 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 AI for beginners course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for project leaders, scrum masters, coaches, product owners, and team members who intend on taking the PMI-ACP© exam. This course provides participants with a foundation of the PMI-ACP© exam. Participants will be introduced to PMI Agile concepts and practices with banks of sample questions. PMI-ACP© Exam Preperation PMI-ACP© Exam Particulars Overview PMI-ACP© Exam Particulars PMI-ACP© Candidate Requirements PMI-ACP© Candidate Fees PMI-ACP© Exam Application Process Core Agile Concepts Core Agile Concepts Overview Traditional Project Management Methodologies Drawbacks of Waterfall Methodologies Agile Approach Empirical Process Control Agile and Traditional Project Management Choice of Methodologies/Frameworks The Agile Manifesto The Agile Manifesto Overview Manifesto Contributors Manifesto Values Manifesto Principles Common Agile Methodology Elements Common Agile Methodology Elements Overview Project (Product; Release) Initiation Agile Planning Iteration Planning and Executing Project Initiation Project Initiation Overview Determine Project Justifications and Metrics Provide Value-Driven Delivery Write Project Vision Statement Create Project Charter Identify Stakeholders and Leader/Coach Form Project Team Agile Teams and Team Space Agile Teams and Team Space Overview Scrum Master/Coach Product Owner/Customer Team Members/Developers (XP) Trackers and Testers Other Roles Team Space Physical Space Recommendations Agile Planning Agile Planning Overview Develop Epics and Stories Create Stories Non-Customer Facing Stories Personas and Extreme Personas Story Maps Estimating Stories Prioritizing Stories Create Product Backlog Create Product Roadmap Conduct Release Planning Create Parking Lot Iterations/Sprints Iterations/Sprints Overview Velocity Determination Iteration Planning Meeting Iteration Planning Guidelines Development Testing Daily Standup Meetings Progress Tracking Velocity Tracking Interpersonal Aspects of Agile Interpersonal Aspects of Agile Overview Methodologies and Uncertainty Coach/Scrum Master Team Motivation Soft Skills Emotional Intelligence Collaboration Negotiations Active listening Conflict Resolution Speed Leas? Model of Group Conflict Conducting Retrospectives Mindsets of Agile Coaches Leadership Stages Key Coaching Responsibilities Agile Methodologies Agile Methodologies Overview XP and Scrum Terms XP Terms and Concepts XP Primary Practices XP Corollary Practices Scrum Lean Software Development Seven Principles of Lean Seven Types of Muda Responsibilities Core Beliefs of Lean-Agile Software Development Other Principles of Lean-Agile Software Development Value Stream Mapping Lean-Agile Software Development Portfolio Management Additional course details: Nexus Humans PMI Agile Certified Practitioner (PMI-ACP) 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 PMI Agile Certified Practitioner (PMI-ACP) 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 Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

Duration 4 Days 24 CPD hours This course is intended for The course content is aimed at operators of devices running the Junos OS in a NOC environment. These operators include network engineers, administrators, support personnel, and reseller support personnel. Overview After successfully completing this course, you should be able to: Reduce the time it takes to identify and isolate the root cause of an issue impacting your network. Gain familiarity with Junos products as they pertain to troubleshooting. Become familiar with online resources valuable to Junos troubleshooting. Gain familiarity with Junos tools used in troubleshooting. Identify and isolate hardware issues. Troubleshoot problems with the control plane. Troubleshoot problems with interfaces and other data plane components. Describe the staging and acceptance methodology. Troubleshoot routing protocols. Describe how to monitor your network with SNMP, RMON, Junos Traffic Vision (formerly known as JFlow), and port mirroring. Become familiar with JTAC procedures. This instructor-led four-day course is designed to provide introductory troubleshooting skills for engineers in a network operations center (NOC) environment. Chapter 1: Course Introduction Course Introduction Chapter 2: Troubleshooting as a Process Before You Begin The Troubleshooting Process Challenging Network Issues The Troubleshooting Process Lab Chapter 3: Junos Product Families The Junos OS Control Plane and Data Plane Field-Replaceable Units Junos Product Families Lab: Identifying Hardware Components Chapter 4: Troubleshooting Toolkit Troubleshooting Tools Best Practices Lab: Using Monitoring Tools and Establishing a Baseline Chapter 5: Hardware and Environmental Conditions Hardware Troubleshooting Overview Memory and Storage Boot Monitoring Hardware-Related System Logs Chassis and Environmental Monitoring Lab: Monitoring Hardware and Environmental Conditions Chapter 6: Control Plane Control Plane Review System and User Processes Monitoring Routing Tables and Protocols Monitoring Bridging Monitoring the Address Resolution Protocol Lab: Control Plane Monitoring and Troubleshooting Chapter 7: Control Plane Protection Protection Overview DDOS Protection Loopback Filter Lab: Control Plane Monitoring and Troubleshooting Chapter 8: Data Plane ? Interfaces Interface Properties General Interface Troubleshooting Ethernet Interface Troubleshooting Lab: Monitoring and Troubleshooting Ethernet Interfaces Chapter 9: Data Plane ? Other Components Definition of a Data Plane Problem Data Plane Components Data Plane Forwarding Load-Balancing Behavior Firewall Filters and Policers Data Plane Troubleshooting Case Study Lab: Isolate and Troubleshoot PFE Issues Chapter 10: Staging and Acceptance Testing Initial Inspection and Power-on General System Checks Interface Testing Chapter 11: Troubleshooting Routing Protocols Troubleshooting OSPF Troubleshooting BGP Troubleshooting Routing Loops and Route Oscillation Lab: Troubleshooting Routing Protocols Chapter 12: High Availability High Availability Overview Graceful Routing Engine Switchover Graceful Restart Nonstop Active Routing and Bridging Unified In-Service Software Upgrade Chapter 13: Network Monitoring SNMP RMON Telemetry Flow Monitoring Lab: Monitoring the Network Chapter 14: vMX Troubleshooting vMX Overview Troubleshooting Lab: Monitoring vMX Chapter 15: JTAC Procedures Opening a Support Case Customer Support Tools The Content of a PR Transferring Files to JTAC Chapter 16: Automated Support and Prevention Overview Service Now Service Insight Lab: Automated Support and Prevention Additional course details: Nexus Humans JTNOC - Junos Troubleshooting in the NOC 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 JTNOC - Junos Troubleshooting in the NOC 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 Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture and main components of NSX Explain the features and benefits of NSX Deploy the NSX Management cluster and VMware NSX Edge™ nodes Prepare VMware ESXi™ hosts to participate in NSX networking Create and configure segments for layer 2 forwarding Create and configure Tier-0 and Tier-1 gateways for logical routing Use distributed and gateway firewall policies to filter east-west and north-south traffic in NSX Configure Advanced Threat Prevention features Configure network services on NSX Edge nodes Use VMware Identity Manager™ and LDAP to manage users and access Explain the use cases, importance, and architecture of Federation This five-day, fast-paced course provides comprehensive training to install, configure, and manage a VMware NSX© environment. This course covers key features and functionality offered in the NSX 4.0.0.1 and NSX 4.0.1 releases, including the overall infrastructure, logical switching, logical routing, networking and security services, firewalls and advanced threat prevention, and more. Course Introduction Introductions and course logistics Course objectives VMware Virtual Cloud Network and VMware NSX Introduce the VMware Virtual Cloud Network vision Describe the NSX product portfolio Discuss NSX features, use cases, and benefits Explain NSX architecture and components Explain the management, control, data, and consumption planes and their functions. Preparing the NSX Infrastructure Deploy VMware NSX© ManagerTM nodes on ESXi hypervisors Navigate through the NSX UI Explain data plane components such as N-VDS/VDS, transport nodes, transport zones, profiles, and more Perform transport node preparation and configure the data plane infrastructure Verify transport node status and connectivity Explain DPU-based acceleration in NSX Install NSX using DPUs NSX Logical Switching Introduce key components and terminology in logical switching Describe the function and types of L2 segments Explain tunneling and the Geneve encapsulation Configure logical segments and attach hosts using NSX UI Describe the function and types of segment profiles Create segment profiles and apply them to segments and ports Explain the function of MAC, ARP, and TEP tables used in packet forwarding Demonstrate L2 unicast packet flow Explain ARP suppression and BUM traffic handling NSX Logical Routing Describe the logical routing function and use cases Introduce the two-tier routing architecture, topologies, and components Explain the Tier-0 and Tier-1 gateway functions Describe the logical router components: Service Router and Distributed Router Discuss the architecture and function of NSX Edge nodes Discuss deployment options of NSX Edge nodes Configure NSX Edge nodes and create NSX Edge clusters Configure Tier-0 and Tier-1 gateways Examine single-tier and multitier packet flows Configure static routing and dynamic routing, including BGP and OSPF Enable ECMP on a Tier-0 gateway Describe NSX Edge HA, failure detection, and failback modes Configure VRF Lite NSX Bridging Describe the function of logical bridging Discuss the logical bridging use cases Compare routing and bridging solutions Explain the components of logical bridging Create bridge clusters and bridge profiles NSX Firewalls Describe NSX segmentation Identify the steps to enforce Zero-Trust with NSX segmentation Describe the Distributed Firewall architecture, components, and function Configure Distributed Firewall sections and rules Configure the Distributed Firewall on VDS Describe the Gateway Firewall architecture, components, and function Configure Gateway Firewall sections and rules NSX Advanced Threat Prevention Explain NSX IDS/IPS and its use cases Configure NSX IDS/IPS Deploy NSX Application Platform Identify the components and architecture of NSX Malware Prevention Configure NSX Malware Prevention for east-west and north-south traffic Describe the use cases and architecture of VMware NSX© Intelligence? Identify the components and architecture of VMware NSX© Network Detection and Response? Use NSX Network Detection and Response to analyze network traffic events. NSX Services Explain and configure Network Address Translation (NAT) Explain and configure DNS and DHCP services Describe VMware NSX© Advanced Load Balancer? architecture, components, topologies, and use cases. Configure NSX Advanced Load Balancer Discuss the IPSec VPN and L2 VPN function and use cases Configure IPSec VPN and L2 VPN using the NSX UI NSX User and Role Management Describe the function and benefits of VMware Identity Manager? in NSX Integrate VMware Identity Manager with NSX Integrate LDAP with NSX Identify the various types of users, authentication policies, and permissions Use role-based access control to restrict user access Explain object-based access control in NSX NSX Federation Introduce the NSX Federation key concepts, terminology, and use cases. Explain the onboarding process of NSX Federation Describe the NSX Federation switching and routing functions. Describe the NSX Federation security concepts.

This very practical one-day IACCM-approved programme enables participants to manage the process of commercial contracting and contract management effectively and efficiently to ensure value for money, improved service, and appropriate relationships. It covers a wide range of contract types in terms of risk and value. The programme empowers participants with the tools and techniques needed to collaborate with all key stakeholders. By the end of the programme participants will be able to: Understand the total process of managing contracts Exploit opportunities to extract even more added value Develop appropriate relationships with contractors Understand and use a range of contracting strategies and options Measure and improve contract performance Understand the impact of legislation on contract performance 1 Welcome Introductions Aims and objectives Plan for the day 2 Contract management An overview of the contracting process, mapping the 'territory' 3 Contract managers Skills Knowledge Attributes Responsibilities 4 Critical success factors Defining successful outcomes Effective stakeholder engagement Creating a shared vision of the outcomes 5 Placing contracts How to develop an effective specification and scope of work documents How to develop a robust contracting strategy Appropriate types of contract 6 Customers and stakeholders Customer and stakeholder analysis Managing expectations and the 'shared vision' concept to ensure customer co-operation, satisfaction, and delight 7 Working with suppliers Creating and developing commercial relationships Types of relationship How to manage difficult relationships Contractor motivational issues How to use incentives 8 Negotiation and related skills Introduction to key negotiation skills Persuading and influencing skills to work with stakeholders to improve outcomes for all 9 Dealing with change Claims and variations How to challenge contractor claims and requests for variations by making use of contractual terms Specifications to prevent false claims 10 Performance improvement How to measure and improve contractor performance Developing KPI systems Using contractual terms and conditions and basic legal principles 11 Contract close The importance of effective contract close processes 12 Close Review of key learning points Personal action planning

Developing the high performing team takes time and effort. But above all, it requires an understanding of the dynamics of high performing teams. This programme helps managers and leaders understand what high performing teams do and how they do it. It focuses on enabling managers to see their teams from different perspectives, allowing them to adapt their styles to maximise team outputs. A core theme is the need for managers of teams to 'hold up the mirror' to themselves and to see themselves as a leader of people, to reflect on how others see them and to modify their style accordingly. This programme will help managers / team leaders: Analyse the constituents of a 'high performing' team Apply essential influencing techniques Use a range of communication techniques to support effective teamwork Create and articulate team vision Generate common values Assess team effectiveness and take/recommend the appropriate actions Make more efficient use of team time Understand and agree on techniques to manage conflict Define and implement team meeting protocols that will facilitate team effectiveness Use the Prime Focus model to create the environment and framework for a high performing team Draft your team strategy to take them to the next level Day 1 1 Welcome and introduction Participants are welcomed to the programme and invited to share their personal objectives and people challenges Participants are given an action plan template to complete throughout the workshop 2 Your team The concept of 'positive intention' The difference between a team and a high performing team Assess your team effectiveness What is your 'interference'? 3 The team environment Setting the scene Building rapport Active listening Team goals and role profiling 4 Your style Tuckman model of team stages - how do you manage each stage? Team standards and goals Your team vision 5 Effective team meetings Influencing in team meetings How to make them interesting and relevant The pure role of the chair Day 2 1 Effective communication techniques Giving and receiving feedback Your communication style How to adapt, pace and lead to build rapport The Mehrabian theory of communication 2 How to manage conflict What is conflict? What is your default conflict approach? Tools and tips for managing conflict Practice sessions 3 Team skills Undertake a team skills analysis Types of team member Motivating team members Reframing situations 4 Setting your strategy Seeing the bigger picture The Prime Focus Model Your strategy for success Articulating your strategy Action plans revisited

Duration 5 Days 30 CPD hours This course is intended for Experienced security administrators or network administrators Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture and main components of NSX-T Data Center Explain the features and benefits of NSX-T Data Center Deploy the NSX Management cluster and VMware NSX Edge™ nodes Prepare VMware ESXi™ and KVM hosts to participate in NSX-T Data Center networking Create and configure segments for layer 2 forwarding Create and configure Tier-0 and Tier-1 gateways for logical routing Use distributed and gateway firewall policies to filter east-west and north-south traffic in NSX-T Data Center Configure Advanced Threat Prevention features Configure network services on NSX Edge nodes Use VMware Identity Manager and LDAP to manage users and access Explain the use cases, importance, and architecture of Federation This five-day, fast-paced course provides comprehensive training on how to install, configure, and manage a VMware NSX-T? Data Center environment. This course covers key NSX-T Data Center features and functionality offered in the NSX-T Data Center 3.2 release, including the overall infrastructure, logical switching, logical routing, networking and security services, firewalls and advanced threat prevention, and more. Course Introduction Introductions and course logistics Course objectives VMware Virtual Cloud Network and NSX-T Data Center Introduce the VMware Virtual Cloud Network vision Discuss NSX-T Data Center solutions, use cases, and benefits Explain NSX-T Data Center architecture and components Describe the VMware NSXTM product portfolio and features Explain the management, control, data, and consumption planes and function Preparing the NSX-T Data Center Infrastructure Describe NSX Management Cluster Deploy VMware NSXTM ManagerTM nodes on VMware ESXi and KVM hypervisors Navigate through the NSX Manager UI Explain data-plane components such as N-VDS/VDS, transport nodes, transport zones, profiles, and more Perform transport node preparation and establish the data center infrastructure Verify transport node status and connectivity NSX-T Data Center Logical Switching Introduce key components and terminology in logical switching Describe the function and types of L2 segments Explain tunneling and the GENEVE encapsulation Configure logical segments and attach hosts using NSX Manager UI Describe the function and types of segment profiles Create segment profiles and apply them to segments and ports Explain the function of MAC, ARP, and TEP tables used in packet forwarding Demonstrate L2 unicast packet flow Explain ARP suppression and BUM traffic handling NSX-T Data Center Logical Routing Describe the logical routing function and use cases Introduce the two-tier routing architecture, topologies, and components Explain the Tier-0 and Tier-1 Gateway functions Describe the logical router components: Service Router and Distributed Router Discuss the architecture and function of NSX Edge nodes Discuss deployment options of NSX Edge nodes Configure NSX Edge nodes and create NSX Edge clusters Configure Tier-0 and Tier-1 Gateways Examine the single-tier and multitier packet flow Configure static routing and dynamic routing, including BGP and OSPF Enable ECMP on Tier-0 Gateway Describe NSX Edge HA, failure detection, and failback modes Configure VRF Lite NSX-T Data Center Bridging Describe the function of logical bridging Discuss the logical bridging use cases Compare routing and bridging solutions Explain the components of logical bridging Create bridge clusters and bridge profiles NSX-T Data Center Firewalls Describe NSX segmentation Identify the steps to enforce Zero-Trust with NSX segmentation Describe the Distributed Firewall architecture, components, and function Configure Distributed Firewall sections and rules Configure the Distributed Firewall on VDS Describe the Gateway Firewall architecture, components, and function Configure Gateway Firewall sections and rules NSX-T Data Center Advanced Threat Prevention Explain NSX IDS/IPS and its use cases Configure NSX IDS/IPS Deploy the NSX Application Platform Identify the components and architecture of NSX Malware Prevention Configure NSX Malware Prevention for east-west and north-south traffic Describe the use cases and architecture of NSX Intelligence Identify the components and architecture of VMware NSX© Network Detection and Response? Use NSX Network Detection and Response to analyze network traffic events. NSX-T Data Center Services Describe NSX-T Data Center services Explain and configure Network Address Translation (NAT) Explain and configure DNS and DHCP services Describe VMware NSX© Advanced Load Balancer? architecture, components, topologies, and use cases. Configure NSX Advanced Load Balancer Discuss the IPSec VPN and L2 VPN function and use cases Configure IPSec VPN and L2 VPN using the NSX Manager UI NSX-T Data Center User and Role Management Describe the function and benefits of VMware Identity Manager? in NSX-T Data Center Integrate VMware Identity Manager with NSX-T Data Center Integrate LDAP with NSX-T Data Center Identify the various types of users, authentication policies, and permissions Use role-based access control to restrict user access NSX-T Data Center Federation Introduce the NSX-T Data Center Federation key concepts, terminology, and use-cases. Explain the onboarding process of NSX-T Data Center Federation Describe the NSX-T Data Center Federation switching and routing functions. Describe the NSX-T Data Center Federation security concepts.

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.