29648 Courses in Cardiff delivered Online

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 1 Days 6 CPD hours This course is intended for This course is designed for students who wish to gain a foundational understanding of PowerPoint that is necessary to create and develop engaging multimedia presentations. Overview In this course, you will create and deliver an engaging PowerPoint presentation. You will: Identify the basic features and functions of PowerPoint. Develop a PowerPoint presentation. Perform text formatting. Add and arrange graphical elements. Modify graphical elements. Prepare to deliver your presentation. How do you grab and maintain an audience's focus when you're asked to present important information? By being clear, organized, and engaging. And, that is exactly what Microsoft© PowerPoint© can help you do.Today's audiences are tech savvy, accustomed to high-impact multimedia content, and stretched for time. By learning how to use the vast array of features and functionality contained within PowerPoint, you will gain the ability to organize your content, enhance it with high-impact visuals, and deliver it with a punch. In this course, you will use PowerPoint to begin creating engaging, dynamic multimedia presentations.Note: Most Office users perform the majority of their daily tasks using the desktop version of the Office software, so that is the focus of this training. The course material will also enable you to access and effectively utilize many web-based resources provided with your Microsoft 365 subscription. This includes brief coverage of key skills for using PowerPoint for the Web and OneDrive. Helpful notes throughout the material alert you to cases where the online version of the application may function differently from the primary, desktop version.This course may be a useful component in your preparation for the Microsoft PowerPoint (Microsoft 365 Apps and Office 2019): Exam MO-300 certification exam. Lesson 1: Getting Started with PowerPoint Topic A: Navigate the PowerPoint Environment Topic B: View and Navigate a Presentation Topic C: Create and Save a Basic Presentation Topic D: Navigate in PowerPoint for the Web Topic E: Use PowerPoint Help Lesson 2: Developing a PowerPoint Presentation Topic A: Create Presentations Topic B: Edit Text Topic C: Work with Slides Topic D: Design a Presentation Lesson 3: Formatting Text Topic A: Format Characters Topic B: Format Paragraphs Lesson 4: Adding and Arranging Graphical Elements Topic A: Insert Images Topic B: Insert Shapes Topic C: Create SmartArt Topic D: Insert Stock Media, Icons, and 3D Models Topic E: Size, Group, and Arrange Objects Lesson 5: Modifying Graphical Elements Topic A: Format Images Topic B: Format Shapes Topic C: Customize SmartArt Topic D: Format Icons Topic E: Format 3D Models Topic F: Animate Objects Lesson 6: Preparing to Deliver Your Presentation Topic A: Review Your Presentation Topic B: Apply Transitions Topic C: Print or Export a Presentation Topic D: Deliver Your Presentation Additional course details: Nexus Humans Microsoft PowerPoint for Office 365 (Desktop or Online) - Part 1 ( v1.1) 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 Microsoft PowerPoint for Office 365 (Desktop or Online) - Part 1 ( v1.1) 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 Change Managers: Responsible for documentation, approval and change processes System Landscape Architects: Responsible for the design of the transport landscape topology System Administrators: Responsible for executing transports Development Managers: Responsible for performing development changes Application Manager: Responsible for approving and performing changes in an application Support Manager and members of the customer's SAP competence center: Responsible for Reporting and Diagnostics capabilities Partners and System Integrators Overview This course will prepare you to: Describe the concept and methods of E2E Change Control Management. Leverage the SAP Solution Manager 7.2 as application platform for E2E Change Control Management. In this course you will learn how change control management coordinates changes that are introduced into a software landscape so that the changes do not conflict with each other and how to make sure the changes are executed without disrupting ongoing business. This results in improved quality of the software landscape, higher availability of IT solutions, and lower total cost of ownership. Also important, change control management ensures that the changes introduced remain transparent, traceable and are made available for reporting and change analysis. Becoming adept at change control management requires skill in the efficient use of standardized methods and procedures. In this ?how to use? training, SAP imparts best-in-class knowledge of solution operations. The End-to-End Change Control Management course introduces participants to what change control management is and the standard tools used to accomplish it, tools provided by SAP Solution Manager. Introduction to E2E Change Control Management Explain the scope of End-to-End Change Control Management Explain the role of SAP Solution Manager to manage changes in your solution landscape Enhanced Change and Transport System Explain how the Enhanced Change and Transport System (CTS+) works Understand the basic concepts of Enterprise Portal and how it is supported by CTS+ Describe the best practices for the setup and usage of CTS+ in different scenarios Configuration Validation Understand the concepts and architecture of E2E Change Diagnostics Find current configuration information with the Change Reporting tool Find recent changes in the solution landscape with the E2E Change Analysis tool Compare multiple systems with the Configuration Validation tool Create targets, use operators and run validation reports Know how to use predefined reports in the report directory Transport and Execution Analysis Service and Transport and Execution Analysis Service for Projects Know how to run and use this self-check services within SAP Solution Manager Understand how to interpret the software change management KPIïs that are collected for your landscape Software Change Strategy Understand the limitations of a three-system landscape Understand the benefits of bundling changes in cycles and synchronized releases Transport Management with SAP Solution Manager Understand the change control landscape concept for transport management in SAP Solution Manager 7.2 Understand the usage of critical objects, cross system object locking and downgrade protection Know how to use retrofit in a dual landscape Understand the features of cCTS, which can be used for Quality Gate Management and Change Request Management parallel to CTS. Quality Gate Management Explain the concept of Solution Transports and Track Synchronization Setup and use Quality Gate Scenario as a central Transport Management Tool Create and release transport requests centrally in SAP Solution Manager for ABAP and Non-ABAP environments Know how to work within the Quality Gate Scenario Change Request Management Understand the different use cases for Change Request Management Describe the various elements of Change Request Management as part of SAP Solution Manager Understand SAP?s best practices for transport management which are implemented in Change Request Management Know how to work with Change Request Management Release Management Learn how to manage Release Management with SAP Solution Manager Understand how to manage the successful deployment of all related changes into the productive environment.

Duration 4 Days 24 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 brand-new 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 adversarial 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 1 Days 6 CPD hours This course is intended for This course is designed for individuals who may need to present information effectively in a professional environment. Overview Define what makes a presentation effective. Plan presentations. Design a presentation framework. Develop the presentation body. Create supporting materials. Prepare for your presentation. Deliver presentations. Conduct a question-and-answer session. Deliver group presentations and virtual presentations. The ability to deliver presentations is vital to achieving advancement for yourself and for your ideas. Few skills in life will contribute to your success as much as presentation skills. Without a dynamic and coherent presentation, even stellar ideas can fail to convince your audience. In this course, you will learn to organize your ideas to create coherent and convincing oral presentations, while also utilizing available visual aids and using public-speaking techniques to strengthen your delivery. Private classes on this topic are available. We can address your organization?s issues, time constraints, and save you money, too. Contact us to find out how. Prerequisites To ensure your success, you will need to have experience writing in a professional context and creating presentations using Microsoft Office PowerPoint. 1. Defining Presentation Effectiveness Identify Qualities of Effective Presentations Evaluate Yourself as a Presenter 2. Planning Presentations Analyze the Audience Establish Your Presentation\'s Objectives 3. Designing the Presentation Create the Presentation Structure Organize the Presentation Body Write the Conclusion First Write the Introduction 4. Developing the Presentation Body Select Evidence Write the Presentation Body Create Visuals 5. Creating Supporting Materials Create a Slide Deck Create Speaker Aids Create Audience Handouts 6. Preparing for Your Presentation Rehearse the Presentation Plan Event Logistics 7. Delivering Presentations Connect with Your Audience Present Powerfully Utilize a Slide Deck Effectively 8. Conducting a Question-and-Answer Session Answer Questions Handle Challenging Questions 9. Presenting in Common Business Scenarios Plan and Deliver a Virtual Presentation Plan and Deliver Group Presentations 10. Key Course Information This course focuses on the skills necessary to prepare and deliver an effective presentation; that being said, the learner will not be creating, delivering, or designing a specific presentation from start to finish in this course (this course only provides the foundational knowledge for doing this work back at the office). This course consists of instructor lecture along with course activities corresponding with the main course objectives. In terms of the course activities, 50% will be discussion based - 25% will be in a group-work format - and 25% will be hands-on/involve a digital tool, such as a PowerPoint or Word file. The intent is for students leaving this course to take the skills learned and apply them to their efforts of creating more effective presentations upon returning to the workplace. Additional course details: Nexus Humans Effective Presentations (Second Edition) 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 Effective Presentations (Second Edition) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine This class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCPs compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Containers and Kubernetes in GCP Create a container using Cloud Build Store a container in Container Registry Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE) Understand how to choose among GCP compute platforms Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pods console output Sign in to a Pod interactively Deployments, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application

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 3 Days 18 CPD hours This course is intended for This class is ideal for integration specialists or Salesforce Administrators who want to learn more about connecting and securing data in Tableau CRM. This course is also great for business analysts or developers interested in creating advanced dashboards. Overview When you complete this course, you will be able to: Determine your user, data, and security requirements, and establish a development process. Set up apps and control what users can do in Tableau CRM by assigning them licenses, permission sets, and app permissions. Load external data to Tableau CRM. Create and run dataflows to load Salesforce data, and join it with data from other datasets. Understand and use Data Sync effectively. Understand Recipes and Data Prep. Understand and implement data security in Tableau CRM, and override security for implementation and testing. Understand how filters on dashboards function and be able to use interactions when necessary. Understand a dashboard's JSON file. Explain the process of dashboard queries and modify a query to meet specific analytic requirements. Modify dataset metadata. Take your Tableau CRM skills to the next level. In this 3-day, expert-led class, you?ll learn how to develop and implement a Tableau CRM environment that contains both Salesforce and non-Salesforce data. Our team of experts will walk you through Tableau CRM features and settings, user setup, how to load and transform data, data security, and how to modify queries to customize dashboards so you can work more efficiently, spot trends, and predict outcomes faster. Discovery and Planning Discovery Meeting Establishing Your Users and Development Process Set Up Users and Apps Overview of User Access on the Tableau CRM Platform Creating Tableau CRM Permission Sets Assigning Licenses and Permission Sets to Users Creating and Sharing Tableau CRM Apps Connect Data Overview of Connecting Data Data Mapping Overview of the Dataflow Process Designing a Dataflow Loading External CSV Data Creating Dataflows Optimizing Dataflows Running, Monitoring, and Scheduling a Dataflow Preparing Datasets with Recipes with Data Prep Data Connectors Additional Transformations Data Security Overview of Security in Tableau CRM Determining Security Requirements Overview of Using Predicate Filters Implementing Ownership-Based Row-Level Security Implementing Role-Based Row-Level Security Implementing Team-Based Row-Level Security Overriding Security for Implementation and Testing Sharing Inheritance Extended Metadata in a Dataset Overview of Extended Metadata (XMD) Updating Field Metadata Adding Quick Action Menus for Records in Tableau CRM Dashboard Templates and Mobile Dashboards Overview of Tableau CRM Dashboard Templates Overview of JSON for Dashboards Building a Dashboard Using a Template Optimizing Dashboards for a Mobile Device Bindings in Dashboards Understanding Filters in Lenses and Dashboards Multi-Dataset Dashboards Filters with Interactions Custom Queries Query Modification Overview of Modifying Queries Maximizing the Use of the Compare Table Salesforce Analytics Query Language (SAQL) SAQL Queries in a Tableau CRM Dashboard Additional course details: Nexus Humans Salesforce Implement and Manage Tableau CRM (ANC301) 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 Salesforce Implement and Manage Tableau CRM (ANC301) 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 installersSystem integratorsSystem administratorsNetwork administratorsSolutions designers Overview After completing this course, you should be able to:Explain transactional service activation and how it relates to business requirementsExplain the benefits and uses of Cisco NSOExplain how Cisco NSO communicates with network devicesUnderstand the NETCONF protocol and be able to read and write simple YANG modelsInstall NSO and describe how NSO uses NETCONF and the Device Manager componentUnderstand the difference between devices that are fully NETCONF capable and those that are less or not NETCONF capableExplain the YANG service model structureDescribe how YANG is used with NSO, create and deploy a service, and explain NSO FASTMAPDesign and manage services with YANG modelsPerform NSO configuration and basic troubleshooting, and describe the following NSO features: integration options, alarms and reporting, scalability and performance options, and available function packsUse logs to troubleshoot the Cisco NSO deployment and check NSO communication with network devicesExplain the mapping logic of service parameters to device models and consequently to device configurationsDescribe the use of different integration options and APIsExplain the use of Reactive FASTMAP for manipulating and implementing advanced Network Functions Virtualization (NFV) componentsDescribe the use of feature components and function packsDefine and explain the European Telecommunications Standards Institute (ETSI) Open Source NFV Management and Orchestration (MANO) principles and solutionWork with the alarm console, and understand the NSO alarm structure and how it conforms to modern network operations procedures The Cisco NSO Essentials for Programmers and Network Architects (NSO201) course introduces you to Cisco© Network Services Orchestrator (NSO). You will learn to install Cisco NSO and use it to manage devices and create services based on YANG templates with XPath. This course provides a brief overview of NSO as a network automation solution, as well as an introduction to NETCONF, YANG, and XPath. You will learn about service packages, network element drivers, and Application Programming Interfaces (APIs). The course also covers service creation, device and configuration management, NSO maintenance, NSO options and integrations, and basic NSO troubleshooting. Introduction to Cisco NSO Meeting Challenges with Orchestration Challenges of Network Management Challenges of Network Orchestration NSO Features and Benefits That Meet Challenges Standardized Approach What Is NSO? Logical Architecture Components What Does NSO Do? Orchestration Use Cases How Does NSO Work? Introduction to NETCONF and YANG Packages Mapping Logic Network Element Drivers (NEDs) Resources and Training Resources Training Get Started with Cisco NSO Installing Cisco NSO Setup Overview Cisco NSO Local Installation Installing NEDs Using NetSim NETCONF Overview Challenges of Network Management Introduction to NETCONF NETCONF Operation Device Manager Device Manager Overview Device Configuration Management Device Connection Management Templates and Groups Other Device Management Tools Service Manager Essentials YANG Overview Introduction to YANG Other Representations of YANG Data Types XPath Overview Basic YANG Statements Can You Spot the Error? Using Services Package Architecture Creating a Service Package Sample Service Configuration Service Template YANG Service Model Deploying a Service Model-to-Model Mapping Mapping Introduction Mapping Logic FASTMAP Template Processing Service Design and Cisco NSO Programmability Service Design Service Design Overview Top-Down Approach Bottom-Up Approach Device Configuration Service Model Service Management Service Management Tasks Service Lifecycle Management Guidelines NSO Programmability Introduction NSO Programmability Overview Python Service Skeleton Creating a Service YANG Model Creating a Service Template Template Processing with Python Cisco NSO Flexibility System Configuration and Troubleshooting System Configuration System Troubleshooting Integration Integration Options NETCONF Server Web Integration SNMP Agent Alarm Management and Reporting Alarm Management Reporting Scalability and Performance High Availability High-Availability Cluster Communications Clustering Layered Service Architecture Addressing Performance Limitations Components and Function Packs Function Packs NFV Orchestration Reactive FASTMAP