25965 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 Cloud Solutions Architects, DevOps Engineers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with a focus on Google Compute Engine. Overview Configure VPC networks and virtual machines Administer Identity and Access Management for resources Implement data storage services in GCP Manage and examine billing of GCP resources Monitor resources using Stackdriver services Connect your infrastructure to GCP Configure load balancers and autoscaling for VM instances Automate the deployment of GCP infrastructure services Leverage managed services in GCP This class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring. Introduction to Google Cloud Platform List the different ways of interacting with GCP Use the GCP Console and Cloud Shell Create Cloud Storage buckets Use the GCP Marketplace to deploy solutions Virtual Networks List the VPC objects in GCP Differentiate between the different types of VPC networks Implement VPC networks and firewall rules Design a maintenance server Virtual Machines Recall the CPU and memory options for virtual machines Describe the disk options for virtual machines Explain VM pricing and discounts Use Compute Engine to create and customize VM instances Cloud IAM Describe the Cloud IAM resource hierarchy Explain the different types of IAM roles Recall the different types of IAM members Implement access control for resources using Cloud IAM Storage and Database Services Differentiate between Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Firestore and Cloud Bigtable Choose a data storage service based on your requirements Implement data storage services Resource Management Describe the cloud resource manager hierarchy Recognize how quotas protect GCP customers Use labels to organize resources Explain the behavior of budget alerts in GCP Examine billing data with BigQuery Resource Monitoring Describe the Stackdriver services for monitoring, logging, error reporting, tracing, and debugging Create charts, alerts, and uptime checks for resources with Stackdriver Monitoring Use Stackdriver Debugger to identify and fix errors Interconnecting Networks Recall the GCP interconnect and peering services available to connect your infrastructure to GCP Determine which GCP interconnect or peering service to use in specific circumstances Create and configure VPN gateways Recall when to use Shared VPC and when to use VPC Network Peering Load Balancing and Autoscaling Recall the various load balancing services Determine which GCP load balancer to use in specific circumstances Describe autoscaling behavior Configure load balancers and autoscaling Infrastructure Automation Automate the deployment of GCP services using Deployment Manager or Terraform Outline the GCP Marketplace Managed Services Describe the managed services for data processing in GCP Additional course details: Nexus Humans Architecting with Google Compute Engine 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 Architecting with Google Compute Engine course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for technology leaders, solution developers, project managers, organizational decision makers, and other individuals seeking to demonstrate a vendor-neutral, cross-industry understanding of ethics in emerging data-driven technologies, such as AI, robotics, IoT, and data science. This course is also designed for professionals who want to pursue the CertNexus Certification Exam CET-110: Certified Ethical Emerging Technologies. Overview In this course, you will incorporate ethics into data-driven technologies such as AI, IoT, and data science. You will: Describe general concepts, theories, and challenges related to ethics and emerging technologies. Identify ethical risks. Practice ethical reasoning. Identify and mitigate safety and security risks. Identify and mitigate privacy risks. Identify and mitigate fairness and bias risks. Identify and mitigate transparency and explainability risks. Identify and mitigate accountability risks. Build an ethical organization. Develop ethical systems in technology-focused organizations. Mutually reinforcing innovations in computing and engineering are catapulting advances in technological production. From blockchain and artificial intelligence (AI) to gene editing and the Internet of Things (IoT), these advances come with tremendous opportunities for improvement in productivity, efficiency, and human well-being. But as scandals increasingly demonstrate, these advances also introduce new and serious risks of conflict and harm.Technology professionals now face growing demands to identify and mitigate ethical risks to human rights and the environment, as well as to navigate ethical tradeoffs between qualities such as privacy and accuracy, fairness and utility, and safety and accountability. This course provides the tools to identify and manage common ethical risks in the development of emerging data-driven technologies. It distills ethical theory, public regulations, and industry best practices into concrete skills and guidelines needed for the responsible development of digital products and services. By following the course's practical, problems-based approach, learners will become adept at applying theories, principles, frameworks, and techniques in their own roles and organizations. Introduction to Ethics of Emerging Technologies Topic A: What?s at Stake Topic B: Ethics and Why It Matters Topic C: Ethical Decision-Making in Practice Topic D: Causes of Ethical Failures Identifying Ethical Risks Topic A: Ethical Reasons Topic B: Stumbling Blocks for Ethical Reasoning Topic C: Identify Ethical Risks in Product Development Topic D: Tools for Identifying Ethical Risks Topic E: Use Regulations, Standards, and Human Rights to Identify Ethical Risks Ethical Reasoning in Practice Topic A: Ethical Theories Topic B: Use Ethical Decision-Making Frameworks Topic C: Select Options for Action Topic D: Avoid Problems in Ethical Decision-Making Identifying and Mitigating Security Risks Topic A: What Is Security? Topic B: Identify Security Risks Topic C: Security Tradeoffs Topic D: Mitigate Security Risks Identifying and Mitigating Privacy Risks Topic A: What Is Privacy? Topic B: Identify Privacy Risks Topic C: Privacy Tradeoffs Topic D: Mitigate Privacy Risks Identifying and Mitigating Fairness and Bias Risks Topic A: What Are Fairness and Bias? Topic B: Identify Bias Risks Topic C: Fairness Tradeoffs Topic D: Mitigate Bias Risks Identifying and Mitigating Transparency and Explainability Risks Topic A: What Are Transparency and Explainability? Topic B: Identify Transparency and Explainability Risks Topic C: Transparency and Explainability Tradeoffs Topic D: Mitigate Transparency and Explainability Risks Identifying and Mitigating Accountability Risks Topic A: What Is Accountability? Topic B: Identify Accountability Risks Topic C: Accountability Tradeoffs Topic D: Mitigate Accountability Risks Building an Ethical Organization Topic A: What Are Ethical Organizations? Topic B: Organizational Purpose Topic C: Ethics Awareness Topic D: Develop Professional Ethics within Organizations Developing Ethical Systems in Technology-Focused Organizations Topic A: Policy and Compliance Topic B: Metrics and Monitoring Topic C: Communication and Stakeholder Engagement Topic D: Ethical Leadership

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 In order to be successful in this class, incoming attendees are required to have current, hands-on experience in developing basic web applications, and be versed in HTML5, CSS3 and JavaScript. This is an intermediate level web development class, designed for experienced web developers, new to Angular, that need to further extend their skills in modern web development. Overview At the end of this five-day course, students will have an application up and running that incorporates components, directives, custom pipes, reactive forms, routes, services, unit testing, and the REST API. They will add authentication, implement the Material library, and learn how to maintain state with NgRX. They will then take a deeper dive including making their own custom directives, lazy loading modules, and E2E testing. They will learn how to enhance their application with animations and create their own Angular library. Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn explore: What Angular is and why should you use it How Angular reduces the amount of code that you must write to add rich functionality to both existing and new web pages What TypeScript is, why it is useful, and how to use it with Angular How to facilitate development and deployment using Angular CLI How to work with the various aspects of the Angular architecture to implement clean, responsive web interfaces How Routers can support navigation within a Single Page Application What the best practices are for using Angular so that it works unobtrusively and performs well How to use Angular with HTTP to support JSON, REST, and other services Working with the Ahead of Time compiler including its impact of developers and the development process How to defend against DOM-based XSS How to manage routing decisions based on pre-defined criteria such as a successful authentication How to meet huge data requirements by processing asynchronous data streams with RxJS Simplify server-side rendering How to facilitate unit testing Enhance an Angular user interface with animations and other advanced features Optimize Angular applications with various tools and techniques Maintain state within an Angular application What Angular 9 brings to the table and its relationship to Angular 8 Mastering Angular is a five-day, hands-on course that thoroughly explores the latest Angular features and advances, demonstrating how to solve the traditional challenges of JavaScript web application development. Throughout the course students will build custom components using application routes, form validation, and unit-testing. The course starts with an introduction of Angular CLI and TypeScript, and then delves into component-driven development with Angular components, covering data-binding, directives, services, routing, HTTP, the RxJS library, forms unit testing, and REST. Students will also learn how to add authentication, use the Material library, learn the NgRX design pattern to implement the NgRX store, make custom directives, enhance their application with animations, write an E2E test, and increase their application's efficiency by lazy loading modules and creating their own Angular library Angular Overview Overview of Angular Architecture Getting Started with Angular Getting Started with TypeScript Bootstrapping with Angular CLI Angular Project Structure Working with Angular Components and Events Third Party Libraries Dynamic Views Pipes Angular Forms Forms and the Forms API Single Page Applications and Routes Single Page Applications Services and Dependency Injection Modules Using RESTful Services Overview of REST Angular and REST Angular Best Practices Angular Style Guide What is New in Angular 9 Reactive Programming in Angular Working with RxJS Security and Authentication DomSanitizer JSON Web Tokens Route Guards Enhancing the Angular App Angular Animations Angular Material Angular Elements Deep Dive into Angular Testing and Angular Deep Dive into Components and Directives Deep Dive into Services and Dependency Injection Optimizing for the Enterprise Lazy Loading Optimizing with Universal Creating Your Own Angular Library Maintain State with NgRX NgRX Store Lesson: ES6+ Sass and SCSS for Angular and Material

The leadership role of the project manager is increasingly recognised as a key determinant in delivering success. These skills can often be critical in project situations, where tight budgets and deadlines demand the highest levels of team performance and where the working environment presents fresh challenges on a daily basis. This programme focuses on the leadership skills required of project managers and will benefit anyone involved in managing projects large or small wishing to extend or enhance those skills. The objectives of this programme are to help the participants: Understand the significance of leadership skills to the project manager and the impact of these skills on project performance Review the key skills needed to be an effective 'multi-dimensional' project leader and learn how to develop, adapt and apply them in practice Learn how to identify the preferred leadership style for the context and organisational culture of a project and how to develop personal style versatility Understand the role of the project leader in building an effective team and the skills required to promote and sustain team performance Gain a better understanding of the interpersonal skills needed to motivate individual team members and harness the full potential of the team DAY ONE 1 Introduction Aims and objectives Personal objectives 2 Project management and leadership What is a leader? How much can leadership be learned? The project environment and the impact of leadership skills The characteristics of high performance project teams and their leaders 3 Principles of effective leadership Some useful models and theories of leadership explored Types of leadership; choosing how to use leadership power Evaluating personal leadership style; how to develop style flexibility 4 Syndicate case study: Leadership in action Review of the role of leadership in a contemporary project Feedback and plenary discussion: effective project leadership 5 Team exercise: Leadership skills of the project manager Teams compete in performing a project simulation Project review and feedback Discussion of the outcome: role and skills of the project leader 6 Leadership skills for project managers The 3 dimensions of project leadership: inwards, outwards, and upwards The vital role of communication skills and how to develop them Developing a 'project vision': strategic thinking skills Understanding others; emotional intelligence skills Being a visible leader; behavioural and influencing skills Building effective relationships; the importance of trust and respect DAY TWO 7 Leading the project team The role of leadership in developing team performance Understanding individual strengths; recognising team role preferences Managing conflict and promoting positive team dynamics Setting standards, maintaining discipline and rewarding performance Harnessing team potential: building motivation within the team Promoting team learning; the team leader as coach / mentor 8 Leading through the organisation Gaining the support others; developing effective influencing skills Getting empowerment from key stakeholders Knowing when and how to take the initiative and lead Building and maintaining rapport with key partners Becoming an effective team player in leadership teams Becoming a business leader; leading colleagues and co-workers 9 Team exercise: Leadership and negotiation Teams engage in a negotiation exercise Exercise review and feedback Discussion of the outcome: negotiation skills of the project leader 10 Negotiation skills for project leaders Characteristics of effective negotiators Classic problem behaviours and mind-sets to avoid Getting to win-win; building partnership and trust 11 Leading more senior stakeholders The challenges and skills of leading and managing upwards Communicating with more senior stakeholders; building credibility Negotiating upwards: knowing when and how The role of networking skills; building and maintaining rapport Handling disagreements; the art of diplomacy Handling personality and style conflicts with more senior people

Many organisations find that project teams struggle to create and maintain effective plans. Estimates are often overly optimistic and risks go unmanaged until the inevitable happens. Resource managers also find it hard to forecast the likely loading on their departments and requests for support are not provided in a consistent format. This programme has been developed to address these needs in a very practical, hands-on format. Case study work can be based on simulations or on the organisation's current projects for maximum benefit to participants. The aim of this training is to develop and enhance participants' planning and risk management skills in order to maximise the success of project work undertaken by the organisation. The principal training objectives for this programme are to: Provide a structured, integrated approach to planning and risk management Demonstrate practical tools and techniques for each stage of planning Show how to organise and involve relevant people in the planning process Explain how to use the plan for forecasting and pro-active project control Identify ways to improve planning, both individually and corporately The course will emphasise the importance of participative planning techniques that improve the quality of plans whilst reducing overall time and cost of planning. The course will encourage discussion of internal procedures and practices and may be customised to include them if required. DAY ONE 1 Introduction (Course sponsor) Why this programme has been developed Review of participants' needs and objectives 2 Projects and planning Why plan? The benefits of good planning / penalties of poor planning Planning in the project lifecycle; the need for a 'living' plan The interaction between target setting and the planning process Team exercise: planning the project 3 Planning the plan Defining the application and structure of the plan Impact of planning decisions during the project lifecycle Using available time to create an effective plan 4 Defining deliverables Assessing the context; reviewing the goals and stakeholders Developing the scope and defining deliverables; scope mapping Understanding customer priorities; delivering value for money Case study: defining the project deliverables 5 Creating the work breakdown Building the work breakdown structure Detailing the tasks and sub-tasks; structured brainstorming Defining task ownership; the task responsibility matrix 6 Creating and using a logical network Developing the logical network; task boarding Determining the critical path and calculating float Accelerating the plan; concurrent programming and risk Individual and group exercises DAY TWO 7 Developing resource schedules Deriving the Gantt chart from the network Developing the detailed resource schedules Calculating the expenditure profile ('S' curve) 8 Estimating task durations and costs Understanding estimates: effort, availability and duration Estimating tools and techniques Application of estimating techniques during the project lifecycle 9 Case study Developing the project plan Refining the project plan Team presentations and discussion 10 Managing risks and refining the plan Awareness of contractual issues associated with risk Identifying and evaluating risks; deciding ownership Managing risks: determining levels of provision and contingency Controlling risks: maintaining an up-to date risk register 11 Planning for pro-active control The earned value analysis (EVA) concept and its predictive value Deriving the measures needed for cost and delivery performance Practical issues associated with implementing EVA 12 Using and maintaining the plan Tracking progress and updating the plan Publishing and controlling the plan 13 Course review and transfer planning (Course sponsor present) Identify ways of implementing the techniques learnt Sponsor-led review and discussion of proposals Conclusion

The 2-day Coaching and Mentoring for Managers course is designed for organisations that want their managers and team leaders to apply practical coaching and mentoring skills in everyday work situations in order to develop the performance of those they are responsible for, as well as improving communication within the business. Previous attendees have included chief executives, general managers, and HR managers, right through to production line supervisors and office staff. In fact, anybody that has to work as part of a team and relies on other people's efforts will benefit from this programme. Course Syllabus The syllabus of the Coaching and Mentoring for Managers course is comprised of four modules, covering the following: Module One Introduction to Coaching and Mentoring Exploding the myths surrounding coaching Benefits of coaching and mentoring The role of a coach and mentor How to avoid everyday interference that takes your time away from coaching people to achieve results How motivation works The difference between mentoring, coaching, directing, supporting & delegating, and learning when it is necessary to apply them Why coaching is an action orientated partnership purely focused on measurable results Coaching and mentoring outcomes Module Two Managing a Coaching Session The most important skills of a business coach The key characteristics of a good coach How to ask powerful coaching questions Opportunity to role-play using the STAR/GROW model Module Three Mentoring in Action Mentoring suggestions The first meeting Between first and second meetings The second meeting The Experiential learning cycle Model discussions Frequent questions asked by Mentors Duration of mentoring End of relationships Module Four Putting Learning into Practice Building a bank of great coaching questions Demonstration of what has been taught in a live coaching/mentoring meeting Individual feedback from a professional coach Creating SMART action plans Getting started as a work coach/mentor Group review and feedback on new learning Action steps for new coaches Scheduled Courses Unfortunately this course is not one that is currently scheduled as an open course, and is only available on an in-house basis. Please contact us for more information.

Duration 3 Days 18 CPD hours This course is intended for This course is for Azure Administrators who migrate and manage SAP solutions on Azure. Azure Administrators manage the cloud services that span storage, networking, and compute cloud capabilities, with a deep understanding of each service across the full IT lifecycle. They take end-user requests for new cloud applications and make recommendations on services to use for optimal performance and scale, as well as provision, size, monitor and adjust as appropriate. This role requires communicating and coordinating with vendors. Azure Administrators use the Azure Portal and as they become more proficient they use PowerShell and the Command Line Interface. Overview After completing this course, students will be able to: Migrate and SAP HANA, S/4HANA, SAP NetWeaver to Azure Leverage Azure Portal, Cloud Shell, Azure PowerShell, CLI, and Resource Manager Use intersite connectivity features including VNet Peering and VNet-to-VNet connections Work with Azure Active Directory (AAD) and Azure AD Connect As an IT Professionals experienced in SAP solutions, you will discover how to leverage Azure resources that include deployment and configuration of virtual machines, virtual networks, storage accounts, and Azure AD that includes implementing and managing hybrid identities. You will also be introduced to concepts, scenarios, procedures, and hands-on labs that will empower you to best plan and implement migration and operation of an SAP solution on Azure. You will also receive guidance on subscriptions, create and scale virtual machines, implement storage solutions, configure virtual networking, back up and share data, connect Azure and on-premises sites, manage network traffic, implement Azure Active Directory, secure identities, and monitor your solution. Introduction Contains an overview of the SAP and Microsoft partnership. Foundations of SAP on Azure Contains brief lessons on Azure compute, Azure storage, Azure networking, SAP HANA for Azure (Large Instances), identity services, governance and manageability, backup and data protection services, and migration services. SAP Certified Offerings on Azure Contains lessons on general prerequisites (SAP support in public cloud environments), deployment options of Azure for SAP workloads, SAP product-specific support for Azure, operating System support of Azure for SAP workloads, storage support of Azure for SAP workloads, networking support for SAP, database support for SAP, high availability and disaster recovery support for SAP, and monitoring requirements for SAP. Lab : Online Lab: Implementing Linux clustering on Azure VMs Lab : Online Lab: Implementing Windows clustering on Azure VMs SAP on Azure Reference Architecture Contains lessons on SAP NetWeaver with AnyDB, SAP S4 HANA, and SAP HANA on Azure (Large Instances) on Azure VMs. Planning for Implementing SAP Solutions on Azure Contains lessons on Azure VM compute, network, and storage considerations. As well as Azure VM high availability and disaster recovery, Azure VM backup considerations, Azure VM monitoring considerations, Azure VM security considerations, and Azure VM authentication and access control considerations. Planning for Migrating SAP Workloads to Azure Contains lessons on strategies for migrating SAP systems to Microsoft Azure and SAP a workload planning and deployment checklist. Implementing Azure VM-based SAP Solutions Contains lessons on Azure VM deployment methodologies, single-instance implementations (2-tier or 3-tier), implementing HA SAP NetWeaver with AnyDB on Azure VMs, implementing HA SAP HANA on Azure VMs, configure the Azure Enhanced Monitoring Extension for SAP, and implementing AD and Azure AD-based authentication. Module 8-Deploying HANA Large Instances (HLI) Contains a lesson on implementing HANA Large Instances (HLI). Migrating SAP Workloads to Azure Contains lessons on migration options, DMO methodologies, cloud migration options, and Very Large Database Migration to Azure. Lab : Online Lab-Implement SAP architecture on Azure VMs running Linux Lab : Online Lab-Implement SAP architecture on Azure VMs running Windows Maintaining SAP on Azure Contains lessons on, remote management, performing backups and restores, OS and workload updates, vertical and horizontal scaling, and Disaster Recovery (DR). Monitoring and Troubleshooting SAP on Azure Contains lessons on monitoring Azure VMs, monitoring SAP HANA on Azure (Large Instances), and integrating SAP solutions with Microsoft cloud services.

Duration 5 Days 30 CPD hours This course is intended for Audience for this course This course is designed for system administrators responsible for creating OpenShift Enterprise instances, deploying applications, creating process customizations, managing instances and projects. Prerequisites for this course Have taken Red Hat Enterprise Linux Administration I and II (RH124 and RH134), or equivalent Red Hat Enterprise Linux© system administration experience Be certified as a Red Hat Certified System Administrator (RHCSA), or equivalent Red Hat Enterprise Linux system administration experience Be certified as a Red Hat Certified Engineer (RHCE©) Overview Learn to install, configure, and manage OpenShift Enterprise by Red Hat instances - OpenShift Enterprise Administration (DO280) prepares the system administrator to install, configure, and manage OpenShift Enterprise by Red Hat© instances. OpenShift Enterprise, Red Hat's platform-as-a-service (PaaS) offering, provides pre-defined deployment environments for applications of all types through its use of container technology. This creates an environment that supports DevOps principles such as reduced time to market and continuous delivery. - In this course, students will learn how to install and configure an instance of OpenShift Enterprise, test the instance by deploying a real world application, and manage projects/applications through hands-on labs. - Course content summary - Container concepts - Configuring resources with the command line interface - Building a pod - Enabling services for a pod - Creating routes - Downloading and configuring images - Rolling back and activating deployments - Creating custom S2I images This course will empower you to install and administer the Red Hat© OpenShift© Container Platform, with hands-on, lab-based materials that show you how to install, configure, and manage OpenShift clusters and deploy sample applications to further understand how developers will use the platform. This course is based on Red Hat© Enterprise Linux© 7.5 and Openshift Container Platform 3.9. OpenShift is a containerized application platform that allows your enterprise to manage container deployments and scale your applications using Kubernetes. OpenShift provides predefined application environments and builds upon Kubernetes to provide support for DevOps principles such as reduced time to market, infrastructure-as-code, continuous integration (CI), and continuous delivery (CD). 1 - INTRODUCTION TO RED HAT OPENSHIFT ENTERPRISE Review features and architecture of OpenShift Enterprise. 2 - INSTALL OPENSHIFT ENTERPRISE Install OpenShift Enterprise and configure a master and node. 3 - EXECUTE COMMANDS Execute commands using the command line interface. 4 - BUILD APPLICATIONS Create, build, and deploy applications to an OpenShift Enterprise instance. 5 - PERSISTENT STORAGE Provision persistent storage and use it for the internal registry. 6 - BUILD APPLICATIONS WITH SOURCE-TO-IMAGE (S2I) Create and build applications with S2I and templates. 7 - MANAGE THE SYSTEM Use OpenShift Enterprise components to manage deployed applications. 8 - CUSTOMIZE OPENSHIFT ENTERPRISE Customize resources and processes used by OpenShift Enterprise. 9 - COMPREHENSIVE REVIEW Practice and demonstrate knowledge and skills learned in the course. 10 - NOTE: Course outline is subject to change with technology advances and as the nature of the underlying job evolves. For questions or confirmation on a specific objective or topic, please contact us. Additional course details: Nexus Humans Red Hat OpenShift Administration II: Operating a Production Kubernetes Cluster (DO280) 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 OpenShift Administration II: Operating a Production Kubernetes Cluster (DO280) 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.