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Duration 3 Days 18 CPD hours This course is intended for Senior Executives CIOs and CTOs Business Intelligence Executives Marketing Executives Data & Business Analytics Specialists Innovation Specialists & Entrepreneurs Academics, and other people interested in Big Data Overview More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection. Big Data Architecture Workshop (BDAW) is a learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, students apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for students to learn techniques for architecting big data systems, not only from Cloudera?s experience but also from the experiences of fellow students. Workshop Application Use Cases Oz Metropolitan Architectural questions Team activity: Analyze Metroz Application Use Cases Application Vertical Slice Definition Minimizing risk of an unsound architecture Selecting a vertical slice Team activity: Identify an initial vertical slice for Metroz Application Processing Real time, near real time processing Batch processing Data access patterns Delivery and processing guarantees Machine Learning pipelines Team activity: identify delivery and processing patterns in Metroz, characterize response time requirements, identify Machine Learning pipelines Application Data Three V?s of Big Data Data Lifecycle Data Formats Transforming Data Team activity: Metroz Data Requirements Scalable Applications Scale up, scale out, scale to X Determining if an application will scale Poll: scalable airport terminal designs Hadoop and Spark Scalability Team activity: Scaling Metroz Fault Tolerant Distributed Systems Principles Transparency Hardware vs. Software redundancy Tolerating disasters Stateless functional fault tolerance Stateful fault tolerance Replication and group consistency Fault tolerance in Spark and Map Reduce Application tolerance for failures Team activity: Identify Metroz component failures and requirements Security and Privacy Principles Privacy Threats Technologies Team activity: identify threats and security mechanisms in Metroz Deployment Cluster sizing and evolution On-premise vs. Cloud Edge computing Team activity: select deployment for Metroz Technology Selection HDFS HBase Kudu Relational Database Management Systems Map Reduce Spark, including streaming, SparkSQL and SparkML Hive Impala Cloudera Search Data Sets and Formats Team activity: technologies relevant to Metroz Software Architecture Architecture artifacts One platform or multiple, lambda architecture Team activity: produce high level architecture, selected technologies, revisit vertical slice Vertical Slice demonstration Additional course details: Nexus Humans Big Data Architecture Workshop 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 Big Data Architecture Workshop 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 Administrators or application owners who are responsible for deploying and managing Kubernetes clusters and workloads Overview By the end of the course, you should be able to meet the following objectives: Describe the VMware Tanzu Mission Control architecture Configure user and group access Create and manage Kubernetes clusters Control access Create image registry, network, quota, security, custom and mutation policies Connect your on-premises vSphere with Tanzu Supervisor to VMware Tanzu Mission Control Create, manage, and back up VMware Tanzu Kubernetes Grid™ clusters Create and manage Amazon Elastic Kubernetes Service clusters Perform cluster inspections Manage packages in your clusters Monitor and secure Kubernetes environments During this two-day course, you focus on using VMware Tanzu© Mission Control? to provision and manage Kubernetes clusters. The course covers how to apply image registry, network, security, quota, custom, and mutation policies to Kubernetes environments. It focuses on how to deploy, upgrade, back up, and monitor Kubernetes clusters on VMware vSphere© with VMware Tanzu©, and it also covers package management using the VMware Tanzu Mission Control catalog. Course Introduction Introduction and course logistics Course Objectives What Is VMware Tanzu Mission Control Describe VMware Tanzu Mission Control Describe vSphere with Tanzu Describe Tanzu Kubernetes Grid Describe VMware Tanzu© for Kubernetes Operations Explain how to request access to VMware Tanzu Mission Control Describe VMware Cloud? services Describe the VMware Cloud services catalog Explain how to access VMware Tanzu Mission Control Identify the components of VMware Tanzu Mission Control Explain the resource hierarchy of VMware Tanzu Mission Control Access, Users, and Groups Explain VMware Cloud services and enterprise federation Describe VMware Cloud services roles Explain multifactor authentication Describe the VMware Tanzu Mission Control UI List the components of the VMware Tanzu Mission Control UI Describe the VMware Tanzu CLI Describe the VMware Tanzu Mission Control API Cluster Lifecycle Management Outline the steps for registering a management cluster to VMware Tanzu Mission Control Discuss what a management cluster is Describe provisioners Explain the purpose of a cloud provider account Describe Amazon Elastic Kubernetes Service Describe Azure Kubernetes Service Workload Clusters Describe Tanzu Kubernetes Grid workload clusters Explain how to create a cluster Explain how to configure a cluster Describe Amazon Elastic Kubernetes Service workload clusters Describe Azure Kubernetes Service workload clusters Explain how to attach a Kubernetes cluster Explain how to verify the connections to the cluster Describe cluster health Policy Management Explain how access policies grant users access to different resources Describe the policy model Describe the available policy types Explain how image registry policies restrict from which image registries container images can be pulled Outline how network policies are applied to clusters Discuss how security policies control deployment of pods in a cluster Discuss how quota policies manage resource consumption in your clusters Discuss how custom policies implement specialized policies that govern your Kubernetes clusters Describe mutation policies Explain how Policy Insights reports VMware Tanzu Mission Control policy issues Control Catalog Describe the VMware Tanzu Mission Control catalog Explain how to install packages Describe cert-manager Explain Service Discovery and ExternalDNS Describe Multus CNI and Whereabouts Describe Fluent-Bit Explain Prometheus and Grafana Describe Harbor Describe Flux Describe Helm Describe Git repositories Tanzu Mission Control Day 2 Operations Describe data protection Describe cluster inspections Explain life cycle management Describe VMware Aria Operations? for Applications Discuss VMware Tanzu© Service Mesh? Advanced edition Describe VMware Aria Cost? powered by CloudHealth©

Duration 5 Days 30 CPD hours This course is intended for Developed for experienced IT Professionals working with Citrix Virtual Apps and Desktops 7.1x. Potential students include administrators, engineers, and architects responsible for the end user workspace, provisioning services environment, and overall health and performance of the solution. Overview How to configure Workspace Environment Management to improve the end user environment and virtual resource consumption Understand Zones in Citrix Virtual Apps and Desktops 7.1x and how to account for user and desktop locations and optimal connection and registration How to build and manage App Layers to minimize image sprawl with Citrix Virtual Apps and Desktops 7.1x Understand and configure HDX channels and protocols for improved performance delivering multimedia and data over network connections Get more value out of your Citrix Virtual Apps and Desktops 7.1x investment through the use of Workspace Environment Management, Provisioning Services, Application Layering, and advanced features. Students leave this course with a good understanding of how to manage more complex solutions such as multizone environments spanning multiple locations with configurations around StoreFront, the Delivery Controllers, and HDX. Students will gain the skills to improve logon times, user personalization, and resource performance through Workspace Environment Management. Also, learn to optimize management of your app and desktop images by building and combining App Layers. End the course by learning to install, configure, and manage Provisioning Services in accordance with leading practices.This course includes a voucher to take the related exam (1Y0-311 Citrix XenApp and XenDesktop 7.15 Advanced Administration) and earn your Citrix Certified Professional - Virtualization (CCP-V) certification. Implementing Redundancy and Scalability StoreFront and Citrix Gateway Site Infrastructure Machines Running the Virtual Delivery Agent Managing a Virtual Apps and Desktops Environment with Multiple Locations Zones VDA Registration in a Multi-Zone Environment Zone Preference Optimal Gateway Routing and Zones Managing StoreFront Store Subscriptions in a Multi- Location Environment StoreFront and Citrix ADC Branding Implementing Backups and Disaster Recovery Backups Disaster Recovery Considerations Disaster Recovery Process Implementing Advanced Authentication Methods Multi-factor Authentication - RADIUS & OTP Multi-factor Authentication - Smart Card Authentication Federated Authentication - ADFS, SAML, and FAS Improving App and Data Security Introduction to Application Security Preventing Jailbreak Attacks Minimizing the Impact of Attacks Securing Machines Running the Virtual Delivery Agent TLS to VDA Encryption GPOs and Citrix Policies Image Management Introduction to Troubleshooting Troubleshooting Methodology Process (Standard Slide) Resource Tools and Utilities Introduction to PowerShell Troubleshooting Access Issues Troubleshooting StoreFront Troubleshooting Citrix Gateway Troubleshooting Delivery Controller Issues Validating FMA Services Troubleshooting VDA Registration Issues Troubleshooting VDA Registration Troubleshooting HDX Connection Issues Troubleshooting HDX Connections Introduction to App Layering App Layering Introduction Architecture and How it Works Creating an OS Layer The OS Layer Creating a Platform Layer The Platform Layer Creating App Layers The App Layers Creating Elastic App and User Layers Elastic App Layering User Layers Deploying a Layered Image using Citrix Virtual Apps and Desktops Using Templates in App Layering Using Layered Images in a Citrix Virtual Apps and Desktops Site Exploring Layer Priority Layer Priority Maintaining an App Layering Environment Updating Layers Maintaining and Updating the App Layering Environment Common App Layering Considerations and Additional Resources Introduction to Workspace Environment Management (WEM) Workspace Environment Management (WEM) Introduction WEM Administration Using WEM to Centralize Managing User Resources with WEM Managing Profiles with WEM Managing Endpoints with the WEM Transformer Feature Using WEM for Performance Optimization Optimizing Machine Performance with WEM Optimizing User Experience with WEM Using WEM to Secure Environments WEM Environments Migrating and Upgrading WEM Migrating to WEM Upgrading a WEM Deployment WEM Multi-Location Considerations

Duration 5 Days 30 CPD hours This course is intended for This course is designed for experienced integration specialists and senior-level developers with experience in application development, messaging middleware applications, and transport protocols such as HTTP and FTP. Overview Describe the features and uses of IBM App Connect Enterprise Develop, deploy, and test message flow applications Generate message flow applications from predefined patterns Use the IBM App Connect Enterprise Toolkit problem determination aids to diagnose and solve development and runtime errors Describe the function and appropriate use of IBM App Connect Enterprise processing nodes Write basic Extended Structured Query Language and Java programs to transform data Use the IBM Graphical Data Mapping editor to transform data Define, use, and test simple XML and Data Format Description Language (DFDL) data models Describe supported transport protocols and how to call them in message flows IBM App Connect Enterprise provides connectivity and universal data transformation in heterogeneous IT environments. It enables businesses of any size to eliminate point-to-point connections and batch processing, regardless of operating system, protocol, and data format. This course teaches you how to use IBM App Connect Enterprise to develop, deploy, and support message flow applications. These applications use various messaging topologies to transport messages between service requesters and service providers, and allow the messages to be routed, transformed, and enriched during processing. In this course, you learn how to construct applications to transport and transform data. The course explores how to control the flow of data by using various processing nodes, and how to use databases and maps to transform and enrich data during processing. You also learn how to construct data models by using the Data Format Description Language (DFDL) Course Outline Introduction to IBM App Connect Enterprise Application development fundamentals Exercise: Importing and testing a message flow Creating message flow applications Exercise: Creating a message flow application Connecting to IBM MQ Exercise: Connecting to IBM MQ Controlling the flow of messages Exercise: Adding flow control to a message flow application Modeling the data Exercise: Creating a DFDL model Processing file data Exercise: Processing file data Using problem determination tools and help resources Exercise: Using problem determination tools Exercise: Implementing explicit error handling Mapping messages with the Graphical Data Mapping editor Referencing a database in a message flow application Exercise: Referencing a database in a map Using Compute nodes to transform messages Exercise: Transforming data by using the Compute and JavaCompute nodes Processing JMS, HTTP, and web service messages Preparing for production Exercise: Creating a runtime-aware message flow Additional course details: Nexus Humans WM668G IBM App Connect Enterprise V11 Application Development 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 WM668G IBM App Connect Enterprise V11 Application Development course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for the following roles: Network engineers Network security engineers Network architects Sales/presales engineers Overview After taking this course, you should be able to: Describe Cisco SD-WAN security functions and deployment options Understand how to deploy on-premises threat prevention Describe content filtering options Implement secure Direct Internet Access (DIA) Explain and implement service chaining Explore Secure Access Service Edge (SASE) and identify use cases Describe Cisco Umbrella Secure Internet Gateway (SIG) and deployment options Implement Cisco Umbrella SIG and Domain Name System (DNS) policies Explore and implement Cloud Access Security Broker (CASB) and identify use cases (including Microsoft 365) Describe how to use Cisco ThousandEyes to monitor cloud services Configure Cisco ThousandEyes to monitor Microsoft 365 applications Examine how to protect and optimize access to the Software as a Service (SaaS) application with Cisco SD-WAN Cloud OnRamp Describe and deploy Cloud OnRamp for multi-cloud, including interconnect and colocation use cases Examine Cisco SD-WAN monitoring capabilities and features with vManage and vAnalytics The Implementing Cisco SD-WAN Security and Cloud Solutions (SDWSCS) v1.0 course is an advanced training course focused on Cisco SD-WAN security and cloud services. Through a series of labs and lectures you will learn about on-box security services, including application-aware enterprise firewall, intrusion prevention, URL filtering, malware protection, and Transport Layer Security (TLS) or Secure Socket Layer (SSL) decryption. You will also learn about cloud integration with multiple cloud service providers across multiple use cases. Additionally, the course labs will allow you to configure and deploy local security services and cloud security services with the Cisco Umbrella Secure Internet Gateway (SIG), as well as integrate the Cisco SD-WAN fabric with a cloud service provider using the Cisco vManage automated workflows. The course lab environment is built using Cisco Catalyst 8000v IOS XE routers and Cisco SD-WAN 20.7 code, and it includes the integration of Cisco FirePOWER Threat Defense for network security and Cisco ThousandEyes for network monitoring. The course will allow you to earn 24 Continuing Education (CE) credits toward recertification. Course Outline Introducing Cisco SD-WAN Security Deploying On-Premises Threat Prevention Examining Content Filtering Exploring Cisco SD-WAN Dedicated Security Options Examining Cisco SASE Exploring Cisco Umbrella SIG Securing Cloud Applications with Cisco Umbrella SIG Exploring Cisco SD-Wan ThousandEyes Optimizing SaaS Applications Connecting Cisco SD-WAN to Public Cloud Examining Cloud Interconnect Solutions Exploring Cisco Cloud OnRamp for Colocation Monitoring Cisco SD-WAN Cloud and Security Solutions Additional course details: Nexus Humans Cisco SD-WAN Security and Cloud Onboarding v1.0 (SDWSCS) 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 SD-WAN Security and Cloud Onboarding v1.0 (SDWSCS) 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 is an introductory level course for experienced software developers seeking to enhance and extend their core web development skillset leveraging JavaScript. Attendees should have practical experience developing basic software applications. This course provides an excellent foundation for continued learning to gain in-demand skills in in-demand skills and technologies such as NodeJS, Angular, React, Redux and more. This course can also be tailored for less experienced or non-developers as needed. Please inquire for details. Overview Throughout this course, students will explore the practical use of the umbrella of technologies that work in conjunction with JavaScript as well as some of the tools, toolkits, and frameworks that can be used in conjunction with web development and deployment. The course thoroughly explores JavaScript and how it is used within the context of web applications, walking students through the different technologies that are used with JavaScript and exploring core aspects of JavaScript in terms of web applications, security, tools, and frameworks. This skills-focused course is approximately 50% hands-on lab to lecture ratio. Our instructors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment guided by our expert team, attendees will learn to: Understand what JavaScript is and how it is used within the context of web applications Work with the different technologies that are the foundation for web applications. Understand and work with the fundamental aspects of JavaScript in terms of web applications, security, tools, and frameworks Learn to how to effectively work with the newest advances in JavaScript such as ES6 and TypeScript Develop code using conventions and optimal constructs for performance Introduction to JavaScript | Modern JavaScript Essentials is a hands-on geared for web developers who need to learn basic JavaScript to use with today's systems and architectures to build sophisticated web interfaces. The training will guide students through a balanced mixture of theory and practical labs to gain core JavaScript development skills and have them explore its related technologies through to the use of tools and libraries to ease the development of advanced web applications. Course attendees will be able to hit the ground running right after class, applying essential JavaScript to projects at both an architectural as well as a line by line coding level. HTML Refresher (optional) HTMLÿ HTML5 CSS Refresher (optional) CSSÿ CSS3 Overview Introduction to JavaScript JavaScript Basics Debugging Tools JavaScript Functions JavaScript Arrays, Math and Date JavaScript Event Handling and the DOM Object-Oriented JavaScript Advanced JavaScript Topics The Next Step TypeScript Introduction to JSON and Ajax JavaScript Best Practices JavaScript Scheduling, Execution, and Security HTML5 JavaScript API Working with XML (Optional) XML DOM Mechanics XSLT Applied Additional course details: Nexus Humans Introduction to JavaScript | Modern JavaScript Essentials (TT4110) 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 Introduction to JavaScript | Modern JavaScript Essentials (TT4110) 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 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 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 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