5069 Courses

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 The target audience for the DevSecOps Practitioner course are professionals including: Anyone focused on implementing or improving DevSecOps practices in their organization Anyone interested in modern IT leadership and organizational change approaches Business Managers Business Stakeholders Change Agents Consultants DevOps Practitioners IT Directors IT Managers IT Team Leaders Product Owners Scrum Masters Software Engineers Site Reliability Engineers System Integrators Tool Providers Overview After completing this course, students will be able to: Comprehend the underlying principles of DevSecOps Distinguish between the technical elements used across DevSecOps practices Demonstrate how practical maturity concepts can be extended across multiple areas. Implement metric-based assessments tied to your organization. Recognize modern architectural concepts including microservice to monolith transitions. Recognize the various languages and tools used to communicate architectural concepts. Contrast the options used to build a DevSecOps infrastructure through Platform as a Service, Server-less construction, and event-driven mediums Prepare hiring practices to recognize and understand the individual knowledge, skills, and abilities required for mature Dev Identify the various technical requirements tied to the DevSecOps pipelines and how those impact people and process choices. Review various approaches to securing data repositories and pipelines. Analyze how monitoring and observability practices contribute to valuable outcomes. Comprehend how to implement monitoring at key points to contribute to actionable analysis. Evaluate how different experimental structures contribute to the 3rd Way. Identify future trends that may affect DevSecOps The DevSecOps Practitioner course is intended as a follow-on to the DevSecOps Foundation course. The course builds on previous understanding to dive into the technical implementation. The course aims to equip participants with the practices, methods, and tools to engage people across the organization involved in reliability through the use of real-life scenarios and case stories. Upon completion of the course, participants will have tangible takeaways to leverage when back in the office such as implementing DevSecOps practices to their organizational structure, building better pipelines in distributed systems, and having a common technological language. This course positions learners to successfully complete the DevSecOps Practitioner certification exam. DevSecOps Advanced Basics Why Advance Practices? General Awareness People-Finding Them Core Process Technology Overview Understanding Applied Metrics Metric Terms Accelerating People-Reporting and Recording Integrating Process Technology Automation Architecting and Planning for DevSecOps Architecture Basics Finding an Architect Reporting and Recording Environments Process Accelerating Decisions Creating a DevSecOps Infrastructure What is Infrastructure? Equipping the Team Design Challenges Monitoring Infrastructure Establishing a Pipeline Pipelines and Workflows Engineers and Capabilities Continuous Engagement Automate and Identify Observing DevSecOps Outcomes Observability vs. Monitoring Who gets which Report? Setting Observation Points Implementing Observability Practical 3rd Way Applications Revisiting 3rd Way Building Experiments Getting the Most from the Experiment The Future of DevOps Looking Towards the Future Staying Trained Innovation What, and from Who? Post-Class Assignments/Exercises Extended advanced reading associated with Case Stories from the course Additional course details: Nexus Humans DevSecOps Practitioner (DevOps Institute) 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 DevSecOps Practitioner (DevOps Institute) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 System administrators System engineers Migration engineers Migration architects Overview By the end of the course, you should be able to meet the following objectives: Describe core VMware HCX use cases and common triggers for mobility Describe the core components and features of VMware HCX Describe a real-life example of a VMware HCX project Identify all major Cloud Providers offering and supporting VMware HCX Describe the features of VMware HCX services Explain the different deployment types for VMware HCX and choose the correct components to deploy for a particular use case Understand the resource, network, and VMware ESXi™ and VMware vCenter requirements for VMware HCX Install and configure VMware HCX Understand, deploy, and manage the HCX Service Mesh Understand Network Extension and Traffic Engineering Create Network Extension and enable Mobility Optimized Networking Understand WAN Optimization Understand the different migration types and be able to choose the best one for different applications and workloads Incorporate VMware HCX into a disaster recovery strategy Design a VMware HCX deployment for different use cases Manage the lifecycle of VMware HCX This four-day course gives you knowledge and practical exercises sufficient to manage VMware HCX© and to migrate virtual machines using VMware HCX. The course focuses on configuration and management of VMware HCX. The course equips system administrators with the knowledge, skills, and abilities to achieve competence in migrating virtual machines. Course Introduction Introductions and course logistics Course objectives Introduction to VMware HCX Describe workload mobility challenges that VMware HCX addresses Recognize use cases for VMware HCX Identify all major Cloud providers offering and supporting VMware HCX HCX Services and Deployment Types Describe the functions of VMware HCX components Recognize the services provided by VMware HCX Recognize when to use different deployment types for VMware HCX Be able to choose which components to install and configure for a different VMware HCX service HCX Deployment Identify the resource, network, and ESXi/VMware vCenter server requirements for VMware HCX Understand the VMware vCenter user roles and access requirements Describe the installation workflow Install, activate, and configure VMware HCX manager Understand the compute and network profile requirements for VMware HCX and its services Create site pair, compute, and network profiles Describe and manage the HCX Service Mesh Create and configure a HCX Service Mesh Network Extension Describe network extension use case and benefits Compare the HCX-Network extension service with other solutions Examine Network Extension capabilities and topology Create a Network Extension Describe network traffic packet flow Describe Mobility Optimized Networking Enable Mobility Optimized Networking Describe the TCP Flow Conditioning and Application path resiliency feature of VMware HCX Recognize the key benefits of TCP flow conditioning and Application path resiliency Describe WAN optimization Workload Mobility Describe different migration types Recognize the limitation of each migration method and consideration when planning a migration Understand Bulk and Replication Assisted VMware HCX© vMotion© migration methods Migrate a VM using Bulk migration Describe cold and vMotion migration method Migrate a VM using HCX vMotion migration Examine non VMware vSphere© workload migration Migrate a VM using an OS assisted migration method Business Continuity and Disaster Recovery Examine disaster recovery concepts Describe disaster recovery networks Plan and create disaster recovery networks Describe VM protection operations Protect, recover, and test recovery and reverse replication of a VM Understand VMware HCX and SRM integration and value HCX Lifecycle Management Backup and restore the VMware HCX manager Locate and access VMware HCX logs Troubleshoot VMware HCX Plan for VMware HCX manager and component updates Customer Design Scenarios Design a VMware HCX deployment Choose workload mobility methods for the migration Discuss customer requirements and proposed design Discuss components, services, and migration methods for the scenario

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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 Experienced Programmers and Systems Administrators. Overview Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. This course is ?skills-centric?, designed to train attendees in core Python and web development skills beyond an intermediate level, coupling the most current, effective techniques with best practices. Working within in an engaging, hands-on learning environment, guided by our expert Python practitioner, students will learn to: ? Create working Python scripts following best practices ? Use python data types appropriately ? Read and write files with both text and binary data ? Search and replace text with regular expressions ? Get familiar with the standard library and its work-saving modules ? Use lesser-known but powerful Python data types ? Create 'real-world', professional Python applications ? Work with dates, times, and calendars ? Know when to use collections such as lists, dictionaries, and sets ? Understand Pythonic features such as comprehensions and iterators ? Write robust code using exception handling An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features. An Overview of Python What is python? 1 -- An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows Editors and IDEs Getting Started Using variables Built-in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings The standard library The sys module Launching external programs Math functions Random numbers The string module Reading CSV data Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the file system Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations 17 ? Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network services Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Parsing command-line options Detecting the current platform Trapping signals Implementing logging Python Timeline Advantages/Disadvantages of Python Getting help with pydoc

Duration 2 Days 12 CPD hours This course is intended for System architects, system administrators, IT managers, VMware partners, and individuals responsible for implementing and managing vSphere architectures who want to deploy vSphere 8.0 into their existing vSphere environment. Overview By the end of the course, you should be able to meet the following objectives: Recognize the importance of key features and enhancements in vSphere 8.0 Describe vCenter Server, VMware ESXi, storage, virtual machine, and security enhancements in vSphere 8.0 Describe the purpose of vSphere Distributed Services Engine Update an ESXi host equipped with a Data Processing Unit (DPU) using vSphere Lifecycle Manager Identify devices supported for system storage on ESXi 8.0 Recognize enhancements to VM hardware compatibility settings VMware vSphere Memory Monitoring and Remediation and the improvements to vSphere DRS Recognize the new Virtual Non-Uniform Memory Access (vNUMA) topology settings of a VM in vSphere Client Use vSphere Lifecycle Manager and Auto Deploy to manage the configuration specifications for the hosts in a cluster Recognize the vSphere Lifecycle Manager and Auto Deploy enhancements in vSphere 8.0 Recognize the cloud benefits that VMware vSphere+ brings to on-premises workloads Recognize technology that is discontinued or deprecated in vSphere 8.0 In this two-day course, you explore the new features and enhancements following VMware vCenter Server 8.0 and VMware ESXi 8.0. Real-world use-case scenarios, hands-on lab exercises, and lectures teach you the skills that you need to effectively implement and configure VMware vSphere 8.0. Course Introduction Introductions and course logistics Course objectives Artificial Intelligence and Machine Learning Describe how device groups support AI and ML in vSphere 8 Describe how device virtualization extensions support AI and ML in vSphere 8 vSphere Distributed Services Engine Describe the benefits of Distributed Services Engine Explain how Distributed Services Engine works Recognize use cases for Distributed Services Engine Install ESXi on a host equipped with a DPU View DPU information in vSphere Client Add an ESXi host equipped with a DPU to a cluster Update an ESXi host equipped with a DPU using vSphere Lifecycle Manager Create a vSphere Distributed Switch for network offloads Add a host with a DPU to the vSphere Distributed Switch Configure a VM to use Uniform Passthrough Mode vSphere and vCenter Management Review the improvements to the communication between vCenter and ESXi hosts Review the enhancements to the vCenter recovery process ESXi Enhancements Describe the function of the central configuration store in ESXi Explain how ConfigStore affects your interaction with ESXi configuration files Recognize the supported system storage partition configuration on ESXi 8.0 Identify devices supported for system storage on ESXi 8.0 Configure an RDMA host local device on ESXi vSphere Storage Describe the vSAN Express Storage Architecture Recognize the benefits of using vSAN Express Storage Architecture Describe the benefits of using NVMe Recognize the support for NVMe devices in vSphere Guest OS and Workloads Review the enhancements of the latest virtual hardware versions Describe the features introduced with virtual hardware version 20 Create a snapshot of a VM with an NVDIMM device Resource Management View energy and carbon emission metrics in vRealize Operations Manager Describe the VMware vSphere Memory Monitoring and Remediation (vMMR) functionality Describe how vMMR enhances the performance of vSphere DRS Security and Compliance Describe how to handle vTPM secrets when cloning a VM Manage OVF templates for VMs that are configured with vTPM Deploy an OVF template with vTPM Describe the enhancements to trusted binary enforcement in ESXi Describe ESXi 8 enhanced security features vSphere Lifecycle Manager Describe the enhancements to life cycle management of standalone ESXi hosts Manage the configuration profiles of ESXi hosts in a cluster with vSphere Lifecycle Manager Use Auto Deploy to boot a host with the desired image and configuration specifications Upgrade multiple ESXi hosts in a cluster in parallel Stage an ESXi host image prior to remediation Auto Deploy Manage custom host certificates using Auto Deploy vSphere with Tanzu Describe the features of the Tanzu Kubernetes Grid 2.0 offering Announcing vSphere+ Describe the functionality and benefits of vSphere+

Duration 5 Days 30 CPD hours This course is intended for Linux system administrators, virtualization administrators, and hybrid infrastructure engineers interested in deploying large-scale virtualization solutions and managing virtual servers in their datacenters, based on the Red Hat Virtualization open virtualization management platform. Overview Configure Red Hat Virtualization Configure networking and storage for use with Red Hat Virtualization Manage user accounts and access to the Red Hat Virtualization environment Install and manage virtual machines in Red Hat Virtualization Use templates for rapid virtual machine deployment Manage virtual machine snapshots and images Migrate virtual machines and explore high-availability options Deploy, configure, manage, and migrate virtual environments Red Hat Virtualization (RH318) teaches you the skills needed to deploy, administer, and operate virtual machines in your organization using Red Hat© Virtualization. Through numerous hands-on exercises, you will demonstrate the ability to deploy and configure the Red Hat Virtualization infrastructure and use it to provision and manage virtual machines. This offering also prepares you for the Red Hat Certified Specialist in Virtualization exam. This course is based on Red Hat Enterprise Virtualization 4.3 and Red Hat Enterprise Linux© 7.6 and 8, as well as Red Hat Hyperconverged Infrastructure for Virtualization 1.6. 1 - Red Hat Virtualization overview Explain the purpose and architecture of Red Hat Virtualization. 2 - Install and configure Red Hat Virtualization Install a minimal Red Hat Virtualization environment and use it to create a virtual machine. 3 - Create and manage datacenters and clusters Organize hypervisors into groups using datacenters and clusters. 4 - Manage user accounts and roles Configure user accounts using a central directory service, then use roles to assign access to resources based on job responsibilities. 5 - Adding physical hosts Add additional Red Hat Virtualization hosts automatically, and move and remove hosts from datacenters as needed. 6 - Scale Red Hat Virtualization infrastructure Add Red Hat Virtualization hosts automatically, configure Red Hat Enterprise Linux hosts when appropriate, and move and remove hosts from data centers as needed. 7 - Manage Red Hat Virtualization networks Separate network traffic into multiple networks on one or more interfaces to improve the performance and security of Red Hat Virtualization. 8 - Manage Red Hat Virtualization storage Create and manage data and ISO storage domains. 9 - Deploy and manage virtual machines Operate virtual machines in the Red Hat Virtualization environment. 10 - Migrate virtual machines Migrate and control automatic migration of virtual machines. 11 - Manage virtual machine images Manage virtual machine snapshots and disk images. 12 - Automating virtual machine deployment Automate deployment of virtual machines by using templates and cloud-init. 13 - Back up and upgrade Red Hat Virtualization Back up, restore, and upgrade the software in a Red Hat Virtualization environment. 14 - Explore high-availability practices Explain procedures to improve the resilience and reliability of Red Hat Virtualization by removing single points of failure and implementing high-availability features. 15 - Perform comprehensive review Demonstrate skills learned in this course by installing and configuring Red Hat Virtualization; using the platform to create and manage virtual machines; and backing up and updating components of Red Hat Virtualization. Additional course details: Nexus Humans Red Hat Virtualization (RH318) 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 Virtualization (RH318) 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 ideal for developers and engineers including: Cloud administrators Cloud solution architects Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview After completing the course, you should be able to: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multitenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud The course, Mulitcloud Management with Cisco© CloudCenter Suite (CLDCCS) v1.0 is an intensive training course that teaches you to securely design, automate, and deploy applications across multiple clouds while optimizing cost and compliance with comprehensive reporting, visibility, and policy-enforcement. Through a combination of lessons with hands-on lab exercises, you will learn to simplify the lifecycle management of multicloud applications, workflows, and their infrastructure Understanding Cloud Transitions Overview of Traditional IT Introducing Cisco CloudCenter Suite Cisco CloudCenter Suite Definition Setting Up Cisco CloudCenter Workload Manager Artifact Repository Overview and Configuration Understanding User Administration and Multitenancy in Cisco CloudCenter Suite Cisco CloudCenter Suite User Roles Grasping Application Modeling in Cisco CloudCenter Workload Manager Model an Application Identifying Resource Placement Callouts and Lifecycle Actions in Cisco CloudCenter Workload Manager Resource Placement and Validation Callout Understanding Application Deployment Framework in Cisco CloudCenter Workload Manager Workload Manager Application Parameters Exploring Application Services in Cisco CloudCenter Workload Manager Application Services Framework Integrating Cisco CloudCenter Workload Manager with Cisco Application-Centric Infrastructure Configure CloudCenter Workload Manager for Cisco ACI Introducing Application Management in Cisco CloudCenter Workload Manager Cisco CloudCenter Workload Manager Actions Library Exploring Advanced Features in CloudCenter Workload Manager Scheduling an Application in Cisco CloudCenter Workload Manager Comprehending Policies and Tagless Governance in CloudCenter Workload Manager Cisco CloudCenter Workload Manager Policies Introducing Action Orchestrator and Cost Optimizer in Cisco CloudCenter Suite Action Orchestrator in Cisco CloudCenter Suite Lab outline Explore Cisco CloudCenter Suite Admin GUI Discover Cisco CloudCenter Workload Manager GUI Create Cisco CloudCenter Workload Manager Repository Design Deployment Environments in Cisco CloudCenter Workload Manager Create Images in Cisco CloudCenter Workload Manager Form Cost Bundles and Usage Plans in Cisco CloudCenter Workload Manager Explore Multitenancy in Cisco CloudCenter Suite Model and Deploy Two-Tier Application Model and Deploy Multitier Application Perfect and Arrange Multitier Application on Docker Model and Deploy Application on Kubernetes Cloud Deploy Application in Hybrid Cloud Arrange Application Using Automated Resource Placement Perform Lifecycle Actions on Deployed Applications Create User-Defined Parameters and Explore Macros Understand Application Services in Cisco CloudCenter Workload Manage Benchmark, Schedule, and Share Applications in Cisco CloudCenter Workload Manager Continuous Integration/Continuous Delivery (CI/CD) Project Board Manage Policies in Cisco CloudCenter Workload Manager Manage System Tags and Governance in Cisco CloudCenter Workload Manager Explore Action Orchestrator Explore Cost Optimizer Additional course details: Nexus Humans Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 2 Days 12 CPD hours This course is intended for This course is intended for network operators, network administrators, network engineers, network architects, security administrators, and security architects responsible for installation, setup, configuration, and administration of the BIG-IP AFM system. This course uses lectures and hands-on exercises to give participants real-time experience in setting up and configuring the BIG-IP Advanced Firewall Manager (AFM) system. Students are introduced to the AFM user interface, stepping through various options that demonstrate how AFM is configured to build a network firewall and to detect and protect against DoS (Denial of Service) attacks. Reporting and log facilities are also explained and used in the course labs. Further Firewall functionality and additional DoS facilities for DNS and SIP traffic are discussed. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Leveraging F5 Support Resources and Tools Module 2: AFM Overview AFM Overview AFM Availability AFM and the BIG-IP Security Menu Packet Processing Rules and Direction Rules Contexts and Processing Inline Rule Editor Module 3: Network Firewall AFM Firewalls Contexts Modes Packet Processing Rules and Direction Rules Contexts and Processing Inline Rule Editor Configuring Network Firewall Network Firewall Rules and Policies Network Firewall Rule Creation Identifying Traffic by Region with Geolocation Identifying Redundant and Conflicting Rules Identifying Stale Rules Prebuilding Firewall Rules with Lists and Schedules Rule Lists Address Lists Port Lists Schedules Network Firewall Policies Policy Status and Management Other Rule Actions Redirecting Traffic with Send to Virtual Checking Rule Processing with Packet Tester Examining Connections with Flow Inspector Module 4: Logs Event Logs Logging Profiles Limiting Log Messages with Log Throttling Enabling Logging in Firewall Rules BIG-IP Logging Mechanisms Log Publisher Log Destination Filtering Logs with the Custom Search Facility Logging Global Rule Events Log Configuration Changes QKView and Log Files SNMP MIB SNMP Traps Module 5: IP Intelligence Overview Feature 1 Dynamic White and Black Lists Black List Categories Feed Lists IP Intelligence Policies IP Intelligence Log Profile IP Intelligence Reporting Troubleshooting IP Intelligence Lists Feature 2 IP Intelligence Database Licensing Installation Configuration Troubleshooting IP Intelligence iRule Module 6: DoS Protection Denial of Service and DoS Protection Overview Device DoS Protection Configuring Device DoS Protection Variant 1 DoS Vectors Variant 2 DoS Vectors Automatic Threshold Configuration Variant 3 DoS Vectors Device DoS Profiles DoS Protection Profile Dynamic Signatures Dynamic Signatures Configuration DoS iRules Module 7: Reports AFM Reporting Facilities Overview Examining the Status of Particular AFM Features Exporting the Data Managing the Reporting Settings Scheduling Reports Examining AFM Status at High Level Mini Reporting Windows (Widgets) Building Custom Widgets Deleting and Restoring Widgets Dashboards Module 8: DoS White Lists Bypassing DoS Checks with White Lists Configuring DoS White Lists tmsh options Per Profile Whitelist Address List Module 9: DoS Sweep Flood Protection Isolating Bad Clients with Sweep Flood Configuring Sweep Flood Module 10: IP Intelligence Shun Overview Manual Configuration Dynamic Configuration IP Intelligence Policy tmsh options Extending the Shun Feature Route this Traffic to Nowhere - Remotely Triggered Black Hole Route this Traffic for Further Processing - Scrubber Module 11: DNS Firewall Filtering DNS Traffic with DNS Firewall Configuring DNS Firewall DNS Query Types DNS Opcode Types Logging DNS Firewall Events Troubleshooting Module 12: DNS DoS Overview DNS DoS Configuring DNS DoS DoS Protection Profile Device DoS and DNS Module 13: SIP DoS Session Initiation Protocol (SIP) Transactions and Dialogs SIP DoS Configuration DoS Protection Profile Device DoS and SIP Module 14: Port Misuse Overview Port Misuse and Service Policies Building a Port Misuse Policy Attaching a Service Policy Creating a Log Profile Module 15: Network Firewall iRules Overview iRule Events Configuration When to use iRules More Information Module 16: Recap BIG-IP Architecture and Traffic Flow AFM Packet Processing Overview