44175 Courses

Duration 5 Days 30 CPD hours This course is intended for Deployment engineer Network engineer Sales engineer Overview After taking this course, you should be able to: Describe the Cisco conferencing architecture including cloud, hybrid, and on-premises conferencing Describe the physical deployment options and deployment models for Cisco Meeting Server, including Cisco Meeting Server 1000, 2000, and virtual machine Configure a Cisco Meeting Server single combined deployment for Web-Real Time Communications (WebRTC) endpoints within the enterprise Use APIs and the Cisco Meeting Server API Guide to configure profiles using Postman and the Webadmin API tool Configure a scalable and resilient deployment of Cisco Meeting Server with three servers for WebRTC endpoints within the enterprise Configure a scalable and resilient deployment of Cisco Meeting Server to support standard Session Initiation Protocol (SIP) and WebRTC connectivity outside the enterprise Configure a scalable and resilient deployment of Cisco Meeting Server to support recording and streaming of conferences Configure Cisco Unified Communications Manager and Cisco Meeting Server to support Rendezvous, Scheduled, and Ad-hoc conferencing for Cisco Unified CM registered endpoints Configure Cisco Meeting Server to integrate with a preconfigured on-premise Microsoft Skype for Business installation Install Cisco TelePresence Management Suite (Cisco TMS) and Cisco TelePresence Management Suite for Microsoft Exchange (Cisco TMSXE) on a single Microsoft Windows 2012 server and connect to an existing SQL environment Install and integrate Cisco Meeting Management with Cisco TMS and Cisco Meeting Server Set up and manage a scheduled conference with Cisco TMS and Cisco Meeting Management Capture and analyze logs from Cisco Meeting Server and Cisco Meeting Manager to diagnose faults, including a SIP connection error The Implementing Cisco Collaboration Conferencing (CLCNF) v1.0 course focuses on Cisco© on-premises conferencing architecture and solutions. You will gain knowledge and skills to design and implement common conferencing deployment scenarios of Cisco Meeting Server, its integration with call control features such as Cisco Unified Communications Manager and Cisco Expressway, and other Cisco collaboration conferencing devices.This course offers lessons and hands-on labs to prepare you for the 300-825 Implementing Cisco Collaboration Conferencing (CLCNF) exam. Course outline Describing Cisco Conferencing Architecture Configuring a Single Combined Deployment Installing Cisco Meeting Server Using APIs with Cisco Meeting Server Configuring a Cisco Meeting Server Scalable and Resilient Deployment Configuring Business to Business (B2B) and WebRTC Firewall Traversal Connectivity for Cisco Meeting Server Configuring Recording and Streaming with Cisco Meeting Server Troubleshooting Cisco Meeting Server Integrating Cisco Meeting Server with Cisco Unified CM Integrating Cisco Meeting Server with Microsoft Skype for Business Installing and Operating Cisco TMS and Cisco TMSXE Installing and Integrating Cisco Meeting Management Additional course details: Nexus Humans Cisco Implementing Cisco Collaboration Conferencing v2.0 (CLCNF) 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 Collaboration Conferencing v2.0 (CLCNF) 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 To fully benefit from this course, you should have three to five years of experience designing and implementing applications that are built on top of Cisco platforms. This course is appropriate for: Network engineers expanding their skill-base to include software and automation Developers expanding expertise in automation and DevOps Solution architects moving to the Cisco ecosystem Infrastructure developers designing hardened production environments The job roles best suited to the material in this course are: Senior network automation engineer Senior software developer Senior system integration programmer Additional job roles that could find this course useful are: Senior infrastructure architect Senior network designer Senior test development engineer Students preparing for Cisco Certified DevNet Professional and Cisco Certified DevNet Specialist - Core certification will also find this material useful. Overview After taking this course, you should be able to: Describe the architectural traits and patterns that improve application maintainability Describe the architectural traits and patterns that improve application serviceability Identify steps to design and build a ChatOps application Implement robust Representational State Transfer (REST) API integrations with network error handling, pagination, and error flow control Describe the necessary steps for securing user and system data in applications Describe the necessary steps for securing applications Identify common tasks in automated application release process Describe best practices for application deployment Describe methodologies for designing distributed systems Describe the concepts of infrastructure configuration management and device automation Utilize Yet Another Next Generation (YANG) data models to describe network configurations and telemetry Compare various relational and nonrelational database types and how to select the appropriate type based on requirements In this course, you will learn how to implement network applications using Cisco© platforms as a base, from initial software design to diverse system integration, as well as testing and deployment automation. The course gives you hands-on experience solving real world problems using Cisco Application Programming Interfaces (APIs) and modern development tools. This course helps you prepare for Cisco DevNet Professional certification and for professional-level network automation engineer roles. COURSE OUTLINE DESIGNING FOR MAINTAINABILITY (SELF-STUDY) DESIGNING FOR SERVICEABILITY (SELF-STUDY) IMPLEMENTING CHATOPS APPLICATION DESCRIBING ADVANCED REST API INTEGRATION SECURING APPLICATION DATA (SELF-STUDY) SECURING WEB AND MOBILE APPLICATIONS (SELF-STUDY) AUTOMATING APPLICATION-RELEASE DEPLOYING APPLICATIONS UNDERSTANDING DISTRIBUTED SYSTEMS ORCHESTRATING NETWORK AND INFRASTRUCTURE MODELING DATA WITH YANG USING RELATIONAL AND NON-RELATIONAL DATABASES (SELF-STUDY) PLEASE NOTE:This class includes lecture sections and self-study sections. In instructor-led classes, lectures are delivered in real-time, either in person or via video conferencing. In e-learning courses, the lectures are on recorded videos. In both versions, you will need to review self-study sections on your own before taking the certification exam. Additional course details: Nexus Humans Cisco Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 and are responsible for designing or deploying Application Delivery Controllers solutions Overview By the end of the course, you should be able to meet the following objectives: Describe the NSX Advanced Load Balancer components and main functions Describe NSX Advanced Load Balancer Global Server Load Balancing architecture Explain NSX Advanced Load Balancer key features and benefits Understand and apply a Global Server Load Balancing design framework Deploy and configure NSX Advanced Load Balancer Global Server Load Balancing infrastructure Explain and Configure Global Server Load Balancing Application components such as Global Server Load Balancing Service, Global Server Load Balancing Pools and Health Monitors with related components Gather relevant information and perform basic troubleshooting of Global Server Load Balancing applications leveraging built-in NSX Advanced Load Balancer tooling Describe and Configure NSX Advanced Load Balancer application and infrastructure monitoring This 3-day course prepares you to lead VMware NSX Advanced Load Balancer (Avi Networks) Global Server Load Balancing design and deployment projects by providing an understanding of general design processes, frameworks and configurations. You look at the design and deployment considerations for Global Server Load Balancing as part of an overall software-defined data center design. This course covers key NSX Advanced Load Balancer (Avi Networks) Global Server Load Balancing features and functionalities offered in the NSX Advanced Load Balancer 18.2 release. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course. 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 Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles, Pools and Health Monitors DNS Foundations Review, discuss and explain DNS fundamentals Describe NSX Advanced Load Balancer DNS and IPAM providers Global Server Load Balancing Introduce Global Server Load Balancing concepts and benefits Explain and configure NSX Advanced Load Balancer infrastructure Explain and configure DNS Virtual Service components Explain and configure GSLB Service Engine Group Describe and configure GSLB Sites Explain and configure basic GSLB Services, to include pools and health monitors Describe GSLB Service Load Balancing algorithms Explain and configure Data and Control Plane-based Health Monitors Describe GSLB Health Monitor Proxy Global Server Load Balancing Advanced Topics Explain and configure advanced GSLB service properties such as different type of pool members, Host Header and TLS SNI extensions handling within GSLB Health Monitors Describe EDNS Client Subnet Describe Geo-aware Global Server Load Balancing Design and configure Geo-aware Global Server Load Balancing Describe and leverage DNS Policies to customize client experience Explain and configure Topology-aware Global Server Load Balancing Explain and configure GSLB 3rd party sites Describe GSLB Health Monitor sharding Describe GSLB Service Engine sizing implications Troubleshooting NSX Advanced Load Balancer GSLB Solution Introduce Infrastructure and Application troubleshooting Concepts Describe Control Plane and Data Plane-based troubleshooting Describe GSLB Infrastructure troubleshooting Describe GSLB Services troubleshooting Explain Health Monitors troubleshooting Describe Geo-aware and Topology-based GSLB Services troubleshooting Explain Application Analytics and Logs Describe Client Logs analysis Leverage CLI for advanced data plane troubleshooting Monitoring NSX Advanced Load Balancer Solution 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

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 5 Days 30 CPD hours This course is intended for This course is designed for Java developers who want to learn more about the specifications that comprise the world of Java Enterprise Edition (Java EE). Overview As a result of attending this course, you should be able to describe most of the specifications in Java EE 7 and create a component with each specification. You will be able to convert a Java SE program into a multi-tiered Java EE application. You should be able to demonstrate these skills: Describe the architecture of multi-tiered Java EE applications. Package Java EE applications and deploy to Red Hat JBoss Enterprise Application Platform with various tools. Create an Enterprise Java Bean instance. Manage the persistence of data using Java Persistence API. Create a web service using JAX-RS. Properly apply context scopes to beans and inject resources into Java Beans. Store and retrieve messages using the Java Messaging Service. Secure a Java EE application. Red Hat Application Development I: Programming in Java EE with exam (AD184) exposes experienced Java Standard Edition (Java SE) developers to the world of Java Enterprise Edition (Java EE). This course is based on Red Hat© Enterprise Application Platform 7.0. This course is a combination of Red Hat Application Development I: Programming in Java EE (AD183) and Red Hat Certified Enterprise Application Developer Exam (EX183). In this course, you will learn about the various specifications that make up Java EE. Through hands-on labs, you will transform a simple Java SE command line application into a multi-tiered enterprise application using various Java EE specifications, including Enterprise Java Beans, Java Persistence API, Java Messaging Service, JAX-RS for REST services, Contexts and Dependency Injection (CDI), and JAAS for securing the application. Transition to multi-tiered applications Describe Java EE features and distinguish between Java EE and Java SE applications. Package and deploying applications to an application server Describe the architecture of a Java EE application server, package an application, and deploy the application to an EAP server. Create Enterprise Java Beans Develop Enterprise Java Beans, including message-driven beans. Manage persistence Create persistence entities with validations. Manage entity relationships Define and manage JPA entity relationships. Create REST services Create REST APIs using the JAX-RS specification. Implement Contexts and Dependency Injection Describe typical use cases for using CDI and successfully implement it in an application. Create messaging applications with JMS Create messaging clients that send and receive messages using the JMS API. Secure Java EE applications Use JAAS to secure a Java EE application. Comprehensive review of Red Hat JBoss Development I: Java EE Demonstrate proficiency of the knowledge and skills obtained during the course. Additional course details: Nexus Humans Red Hat Application Development I: Programming in Java EE with exam (AD184) 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 Red Hat Application Development I: Programming in Java EE with exam (AD184) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS 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 The Machine Learning Pipeline on AWS 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 System architects and system administrators Overview By the end of the course, you should be able to meet the following objectives: Introduce troubleshooting principles and procedures Use command-line interfaces, log files, and the vSphere Client to diagnose and resolve problems in the vSphere environment Explain the purpose of common vSphere log files Identify networking issues based on reported symptoms Validate and troubleshoot the reported networking issue Identify the root cause of networking issue Implement the appropriate resolution to recover from networking problems Analyze storage failure scenarios using a logical troubleshooting methodology identify the root cause of storage failure Apply the appropriate resolution to resolve storage failure problems Troubleshoot vSphere cluster failure scenarios Analyze possible vSphere cluster failure causes Diagnose common VMware vSphere High Availability problems and provide solutions Identify and validate VMware ESXiTM host and VMware vCenter problems Analyze failure scenarios of ESXi host and vCenter problems Select the correct resolution for the failure of ESXi host and vCenter problems Troubleshoot virtual machine problems, including migration problems, snapshot problems, and connection problems Troubleshoot performance problems with vSphere components This five-day training course provides you with the knowledge, skills, and abilities to achieve competence in troubleshooting the VMware vSphere© 8 environment. This course increases your skill level and competence in using the command-line interface, VMware vSphere© Client?, log files, and other tools to analyze and solve problems. Course Introduction Introductions and course logistics Course objectives Introduction to Troubleshooting Define the scope of troubleshooting Use a structured approach to solve configuration and operational problems Apply troubleshooting methodology to logically diagnose faults and improve troubleshooting efficiency Troubleshooting Tools Discuss the various methods to run commands Discuss the various ways to access ESXi Shell Use commands to view, configure, and manage your vSphere components Use the vSphere CLI Use ESXCLI commands from the vSphere CLI Use Data Center CLI commands Identify the best tool for command-line interface troubleshooting Identify important log files for troubleshooting vCenter Server and ESXi Describe the benefits and capabilities of VMware SkylineTM Explain how VMware Skyline works Describe VMware SkylineTM Health Describe VMware Skyline AdvisorTM Troubleshooting Virtual Networking Analyze and troubleshoot standard switch problems Analyze and troubleshoot virtual machine connectivity problems Analyze and troubleshoot management network problems Analyze and troubleshoot distributed switch problems Troubleshooting Storage Discuss the vSphere storage architecture Identify the possible causes of problems in the various types of datastores Analyze the common storage connectivity and configuration problems Discuss the possible storage problems causes Solve the storage connectivity problems, correct misconfigurations, and restore LUN visibility Review vSphere storage architecture and functionality necessary to troubleshoot storage problems Use ESXi and Linux commands to troubleshoot storage problems Analyze log file entries to identify the root cause of storage problems Investigate ESXi storage issues Troubleshoot VM snapshots Troubleshoot storage performance problems Review multipathing Identify the common causes of missing paths, including PDL and APD conditions Solve the missing path problems between hosts and storage devices Troubleshooting vSphere Clusters Identify and troubleshoot vSphere HA problems Analyze and solve vSphere vMotion problems Diagnose and troubleshoot common vSphere DRS problems Troubleshooting Virtual Machines Discuss virtual machine files and disk content IDs Identify, analyze, and solve virtual machine snapshot problems Troubleshoot virtual machine power-on problems Identify possible causes and troubleshoot virtual machine connection state problems Diagnose and recover from VMware Tools installation failures Troubleshooting vCenter Server and ESXi Analyze and solve vCenter Server service problems Diagnose and troubleshoot vCenter Server database problems Use vCenter Server Appliance shell and the Bash shell to identify and solve problems Identify and troubleshoot ESXi host problems

Duration 5 Days 30 CPD hours This course is intended for Senior Red Hat Enterprise Linux system administrators responsible for the management of multiple servers Overview - Verify a Red Hat Satellite 6.6 installation. - Regulate Red Hat Satellite with organizations, locations, users, and roles. - Manage software with Red Hat Satellite environments and content views. - Use Red Hat Satellite to configure hosts with Ansible playbooks and roles. - Provision hosts with integrated software and configuration management. - Implement Metal-as-a-Service (MaaS) with Satellite discovery and provisioning of unprovisioned hosts. Red Hat Satellite 6 Administration (RH403) is a lab-based course that explores the concepts and methods necessary for successful large-scale management of Red Hat© Enterprise Linux© systems. You will learn how to configure Red Hat Satellite 6 on a server and populate it with software packages. You will use Red Hat Satellite to manage the software development life cycle of a subscribed host and its configuration, and learn how to provision hosts integrated with software and Ansible© configuration management upon deployment. This course is based on Red Hat Enterprise Linux 8 and Red Hat Satellite 6.6. 1 - Plan and deploy Red Hat Satellite Plan and deploy Red Hat Satellite Plan a Red Hat Satellite deployment, then perform installation and initial configuration of Red Hat Satellite servers. 2 - Manage software life cycles Create and manage Red Hat software deployment life cycle environments. 3 - Register hosts Register and configure your Red Hat Enterprise Linux systems to use Red Hat Satellite, then organize those systems into groups for easier management. 4 - Deploy software to hosts Manage software deployment to registered hosts of your Red Hat Satellite infrastructure and practice managing environment paths, life cycle environments, and content views. 5 - Deploy custom software Create, manage, and deploy custom software products and repositories. 6 - Deploy Satellite capsule servers Perform installation and initial configuration of Red Hat Satellite capsule servers as components of a deployment plan. 7 - Run remote execution commands Configure the ability to run ad hoc and scheduled tasks on managed hosts using a variety of configuration management tools. 8 - Provision hosts Configure Satellite server for host deployment and perform host provisioning. 9 - Manage Red Hat Satellite using the API Integrate Red Hat Satellite functionality with custom scripts or external applications that access the API over HTTP. 10 - Plan a Red Hat Satellite deployment on a cloud platform Plan a Red Hat Satellite deployment, installation, and initial configuration on a cloud platform. 11 - Perform Red Hat Satellite server maintenance Manage Red Hat Satellite for security, recoverability, and growth. 12 - Comprehensive review Install and configure Red Hat Satellite Server, then provision content hosts. Additional course details: Nexus Humans Red Hat Satellite 6 Administration (RH403) 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 Red Hat Satellite 6 Administration (RH403) 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 1 Days 6 CPD hours This course is intended for This course is intended for the following participants:Cloud professionals interested in taking the Data Engineer certification exam.Data engineering professionals interested in taking the Data Engineer certification exam. Overview This course teaches participants the following skills: Position the Professional Data Engineer Certification Provide information, tips, and advice on taking the exam Review the sample case studies Review each section of the exam covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate Connect candidates to appropriate target learning This course will help prospective candidates plan their preparation for the Professional Data Engineer exam. The session will cover the structure and format of the examination, as well as its relationship to other Google Cloud certifications. Through lectures, quizzes, and discussions, candidates will familiarize themselves with the domain covered by the examination, to help them devise a preparation strategy. Rehearse useful skills including exam question reasoning and case comprehension. Tips and review of topics from the Data Engineering curriculum. Understanding the Professional Data Engineer Certification Position the Professional Data Engineer certification among the offerings Distinguish between Associate and Professional Provide guidance between Professional Data Engineer and Associate Cloud Engineer Describe how the exam is administered and the exam rules Provide general advice about taking the exam Sample Case Studies for the Professional Data Engineer Exam Flowlogistic MJTelco Designing and Building (Review and preparation tips) Designing data processing systems Designing flexible data representations Designing data pipelines Designing data processing infrastructure Build and maintain data structures and databases Building and maintaining flexible data representations Building and maintaining pipelines Building and maintaining processing infrastructure Analyzing and Modeling (Review and preparation tips) Analyze data and enable machine learning Analyzing data Machine learning Machine learning model deployment Model business processes for analysis and optimization Mapping business requirements to data representations Optimizing data representations, data infrastructure performance and cost Reliability, Policy, and Security (Review and preparation tips) Design for reliability Performing quality control Assessing, troubleshooting, and improving data representation and data processing infrastructure Recovering data Visualize data and advocate policy Building (or selecting) data visualization and reporting tools Advocating policies and publishing data and reports Design for security and compliance Designing secure data infrastructure and processes Designing for legal compliance Resources and next steps Resources for learning more about designing data processing systems, data structures, and databases Resources for learning more about data analysis, machine learning, business process analysis, and optimization Resources for learning more about data visualization and policy Resources for learning more about reliability design Resources for learning more about business process analysis and optimization Resources for learning more about reliability, policies, security, and compliance Additional course details: Nexus Humans Preparing for the Professional Data Engineer Examination 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 Preparing for the Professional Data Engineer Examination 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.