1678 Environment courses delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators or network administrators, Network professionals who have experience working with VMware NSX Advanced Load Balancer and are responsible for designing or deploying Application Delivery Controllers solutions Overview By the end of the course, you should be able to meet the following objectives: Describe the NSX Advanced Load Balancer components and main functions Describe NSX Advanced Load Balancer Global Server Load Balancing architecture Explain NSX Advanced Load Balancer key features and benefits Understand and apply a Global Server Load Balancing design framework Deploy and configure NSX Advanced Load Balancer Global Server Load Balancing infrastructure Explain and Configure Global Server Load Balancing Application components such as Global Server Load Balancing Service, Global Server Load Balancing Pools and Health Monitors with related components Gather relevant information and perform basic troubleshooting of Global Server Load Balancing applications leveraging built-in NSX Advanced Load Balancer tooling Describe and Configure NSX Advanced Load Balancer application and infrastructure monitoring This 3-day course prepares you to lead VMware NSX Advanced Load Balancer (Avi Networks) Global Server Load Balancing design and deployment projects by providing an understanding of general design processes, frameworks and configurations. You look at the design and deployment considerations for Global Server Load Balancing as part of an overall software-defined data center design. This course covers key NSX Advanced Load Balancer (Avi Networks) Global Server Load Balancing features and functionalities offered in the NSX Advanced Load Balancer 18.2 release. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and functions Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles, Pools and Health Monitors DNS Foundations Review, discuss and explain DNS fundamentals Describe NSX Advanced Load Balancer DNS and IPAM providers Global Server Load Balancing Introduce Global Server Load Balancing concepts and benefits Explain and configure NSX Advanced Load Balancer infrastructure Explain and configure DNS Virtual Service components Explain and configure GSLB Service Engine Group Describe and configure GSLB Sites Explain and configure basic GSLB Services, to include pools and health monitors Describe GSLB Service Load Balancing algorithms Explain and configure Data and Control Plane-based Health Monitors Describe GSLB Health Monitor Proxy Global Server Load Balancing Advanced Topics Explain and configure advanced GSLB service properties such as different type of pool members, Host Header and TLS SNI extensions handling within GSLB Health Monitors Describe EDNS Client Subnet Describe Geo-aware Global Server Load Balancing Design and configure Geo-aware Global Server Load Balancing Describe and leverage DNS Policies to customize client experience Explain and configure Topology-aware Global Server Load Balancing Explain and configure GSLB 3rd party sites Describe GSLB Health Monitor sharding Describe GSLB Service Engine sizing implications Troubleshooting NSX Advanced Load Balancer GSLB Solution Introduce Infrastructure and Application troubleshooting Concepts Describe Control Plane and Data Plane-based troubleshooting Describe GSLB Infrastructure troubleshooting Describe GSLB Services troubleshooting Explain Health Monitors troubleshooting Describe Geo-aware and Topology-based GSLB Services troubleshooting Explain Application Analytics and Logs Describe Client Logs analysis Leverage CLI for advanced data plane troubleshooting Monitoring NSX Advanced Load Balancer Solution Describe NSX Advanced Load Balancer Events Describe and configure NSX Advanced Load Balancer Alerts Describe NSX Advanced Load Balancer monitoring capabilities leveraging SNMP, Syslog and Email

Duration 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 Experienced system administrators System engineers System integrators Overview By the end of the course, you should be able to meet the following objectives: Introduce troubleshooting principles and procedures Practice Linux commands that aid in the troubleshooting process Use command-line interfaces, log files, and the vSphere Client to diagnose and resolve problems in the vSphere environment Explain the purpose of key vSphere log files Monitor and optimize compute, network, and storage performance on ESXi hosts Monitor and optimize vCenter Server performance Identify networking problems based on reported symptoms, validate and troubleshoot the reported problem, identify the root cause and implement the appropriate resolution Analyze storage failure scenarios using a logical troubleshooting methodology, identify the root cause, and apply the appropriate resolution to resolve the problem Troubleshoot vSphere cluster failure scenarios and analyze possible causes Diagnose common VMware vSphere High Availability problems and provide solutions Identify and validate VMware ESXi™ host and VMware vCenter Server problems, analyze failure scenarios, and select the correct resolution Troubleshoot virtual machine problems, including migration problems, snapshot problems, and connection problems Troubleshoot performance problems with vSphere components This five-day, accelerated, hands-on training course is a blend of the VMware vSphere: Optimize and Scale and VMware vSphere: Troubleshooting courses. This Fast Track course includes topics from each of these advanced courses to equip experienced VMware administrators with the knowledge and skills to effectively optimize and troubleshoot vSphere at an expert level. Course Introduction Introductions and course logistics Course objectives Introduction to Troubleshooting Define the scope of troubleshooting Use a structured approach to solve configuration and operational problems Apply a troubleshooting methodology to logically diagnose faults and improve troubleshooting efficiency Troubleshooting Tools Use command-line tools (such as Linux commands, vSphere CLI, ESXCLI) to identify and troubleshoot vSphere problems Identify important vSphere log files and interpret the log file contents Network Optimization Explain performance features of network adapters Explain the performance features of vSphere networking Use esxtop to monitor key network performance metrics Troubleshooting Virtual Networking Analyze and resolve standard switch and distributed switch problems Analyze virtual machine connectivity problems and fix them Examine common management network connectivity problems and restore configurations Storage Optimization Describe storage queue types and other factors that affect storage performance Use esxtop to monitor key storage performance metrics Troubleshooting Storage Troubleshoot and resolve storage (iSCSI, NFS, and VMware vSphere© VMFS) connectivity and configuration problems Analyze and resolve common VM snapshot problems Identify multipathing-related problems, including common causes of permanent device loss (PDL) and all paths down (APD) events and resolve these problems CPU Optimization Explain the CPU scheduler operation and other features that affect CPU performance Explain NUMA and vNUMA support Use esxtop to monitor key CPU performance metrics Memory Optimization Explain ballooning, memory compression, and host-swapping techniques for memory reclamation when memory is overcommitted Use esxtop to monitor key memory performance metrics Troubleshooting vSphere Clusters Identify and recover from problems related to vSphere HA Analyze and resolve VMware vSphere© vMotion© configuration and operational problems Analyze and resolve common VMware vSphere© Distributed Resource Scheduler? problems Troubleshooting Virtual Machines Identify possible causes and resolve virtual machine power-on problems Troubleshoot virtual machine connection state problems Resolve problems seen during VMware Tools? installations vCenter Server Performance Optimization Describe the factors that influence vCenter Server performance Use VMware vCenter© Server Appliance? tools to monitor resource use Troubleshooting vCenter Server and ESXi Analyze and fix problems with vCenter Server services Analyze and fix vCenter Server database problems Examine ESXi host and vCenter Server failure scenarios and resolve the problems

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

Duration 5 Days 30 CPD hours This course is intended for Deployment engineer Network engineer Sales engineer Overview After taking this course, you should be able to: Describe the Cisco conferencing architecture including cloud, hybrid, and on-premises conferencing Describe the physical deployment options and deployment models for Cisco Meeting Server, including Cisco Meeting Server 1000, 2000, and virtual machine Configure a Cisco Meeting Server single combined deployment for Web-Real Time Communications (WebRTC) endpoints within the enterprise Use APIs and the Cisco Meeting Server API Guide to configure profiles using Postman and the Webadmin API tool Configure a scalable and resilient deployment of Cisco Meeting Server with three servers for WebRTC endpoints within the enterprise Configure a scalable and resilient deployment of Cisco Meeting Server to support standard Session Initiation Protocol (SIP) and WebRTC connectivity outside the enterprise Configure a scalable and resilient deployment of Cisco Meeting Server to support recording and streaming of conferences Configure Cisco Unified Communications Manager and Cisco Meeting Server to support Rendezvous, Scheduled, and Ad-hoc conferencing for Cisco Unified CM registered endpoints Configure Cisco Meeting Server to integrate with a preconfigured on-premise Microsoft Skype for Business installation Install Cisco TelePresence Management Suite (Cisco TMS) and Cisco TelePresence Management Suite for Microsoft Exchange (Cisco TMSXE) on a single Microsoft Windows 2012 server and connect to an existing SQL environment Install and integrate Cisco Meeting Management with Cisco TMS and Cisco Meeting Server Set up and manage a scheduled conference with Cisco TMS and Cisco Meeting Management Capture and analyze logs from Cisco Meeting Server and Cisco Meeting Manager to diagnose faults, including a SIP connection error The Implementing Cisco Collaboration Conferencing (CLCNF) v1.0 course focuses on Cisco© on-premises conferencing architecture and solutions. You will gain knowledge and skills to design and implement common conferencing deployment scenarios of Cisco Meeting Server, its integration with call control features such as Cisco Unified Communications Manager and Cisco Expressway, and other Cisco collaboration conferencing devices.This course offers lessons and hands-on labs to prepare you for the 300-825 Implementing Cisco Collaboration Conferencing (CLCNF) exam. Course outline Describing Cisco Conferencing Architecture Configuring a Single Combined Deployment Installing Cisco Meeting Server Using APIs with Cisco Meeting Server Configuring a Cisco Meeting Server Scalable and Resilient Deployment Configuring Business to Business (B2B) and WebRTC Firewall Traversal Connectivity for Cisco Meeting Server Configuring Recording and Streaming with Cisco Meeting Server Troubleshooting Cisco Meeting Server Integrating Cisco Meeting Server with Cisco Unified CM Integrating Cisco Meeting Server with Microsoft Skype for Business Installing and Operating Cisco TMS and Cisco TMSXE Installing and Integrating Cisco Meeting Management Additional course details: Nexus Humans Cisco Implementing Cisco Collaboration Conferencing v2.0 (CLCNF) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cisco Implementing Cisco Collaboration Conferencing v2.0 (CLCNF) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the The Machine Learning Pipeline on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This course is designed for students looking to establish a foundational understanding of Access, including the skills necessary to create a new database, construct data tables, design forms and reports, and create queries. Overview In this course, you will create and manage an Access database. You will: Navigate within the Access application environment, create a simple database, and customize Access configuration options. Organize and manage data stored within Access tables. Use queries to join, sort, and filter data from different tables. Use forms to make it easier to view, access, and input data. Create and format custom reports. Data is everywhere. Most job roles today involve some form of data management. Virtually everyone is affected in some way by the need to manage data. A relational database application such as Microsoft© Access© can help you and your organization with this task. This course is the first part of a three-course series that covers the skills needed to perform database design and development in Access. Microsoft© Access© for Office 365?: Part 1 (this course): Focuses on the design and construction of an Access database?viewing, navigating, searching, and entering data in a database, as well as basic relational database design and creating simple tables, queries, forms, and reports. Microsoft© Access© for Office 365?: Part 2 : Focuses on optimization of an Access database, including optimizing performance and normalizing data, data validation, usability, and advanced queries, forms, and reports. Microsoft© Access© for Office 365?: Part 3 : Focuses on managing the database and supporting complex database designs, including import and export of data, using action queries to manage data, creating complex forms and reports, macros and VBA, and tools and strategies to manage, distribute, and secure a database. This course may be a useful component in your preparation for the Microsoft Access Expert (Microsoft 365 Apps and Office 2019): Exam MO-500 certification exam. Lesson 1: Working with an Access Database Topic A: Launch Access and Open a Database Topic B: Use Tables to Store Data Topic C: Use Queries to Combine, Find, Filter, and Sort Data Topic D: Use Forms to View, Add, and Update Data Topic E: Use Reports to Present Data Topic F: Get Help and Configure Options in Access Lesson 2: Creating Tables Topic A: Plan an Access Database Topic B: Start a New Access Database Topic C: Create a New Table Topic D: Establish Table Relationships Lesson 3: Creating Queries Topic A: Create Basic Queries Topic B: Add Calculated Columns in a Query Topic C: Sort and Filter Data in a Query Lesson 4: Creating Forms Topic A: Start a New Form Topic B: Enhance a Form Lesson 5: Creating Reports Topic A: Start a New Report Topic B: Enhance Report Layout Additional course details: Nexus Humans Microsoft Access for Office 365: Part 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 Access for Office 365: Part 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 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training 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 Cloudera Data Scientist Training course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is 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