3896 Courses in Cardiff delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for This is an intermediate level training course, designed for experienced Java developers and architects who need to identify, design, and implement web services. We will explore and apply the terminology, the specification, the processes and technologies specific to web services. Students should have at least a year of practical development experience with Java and servlets, and should be familiar with XML and JSON. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core RESTful development skills, coupling the most current, effective techniques with the soundest industry practices. Working within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand and apply the basic concepts of REST Understand and intelligently discuss the similarities and differences between RESTful services and SOAP-based services Appreciate the security concerns associated with RESTful services Design, develop, and deploy real-world RESTful Services Effectively define and design endpoints Work with query parameters Determine the best format to use for exchanging data Understand the principles associated with HTTP methods and how to stay congruent to them Extend the semantics of the RESTful service beyond the HTTP methods Implement RESTful services using JAX-RS to Handle various HTTP methods Use different approaches for parameters Deal with content negotiation Work with different data formats including XML and JSON Handle exceptions Implement RESTful Java clients Develop JAX-RS Java clients using the JAX-RS 2.0 Client API Manage different Web targets Deal with content negotiation on the client Work with different data formats including XML and JSON Properly process server responses Implement JAX-RS Filters and Interceptors Intercept and manipulate service requests and responses Dynamically register interceptor to resources Understand the concept of NameBinding Discover asynchronous JAX-RS processing Implement an asynchronous JAX-RS service endpoint Register response listeners Geared for experienced Java developers, Java REST Essentials is a two day, lab-intensive services training course that introduces developers to the core concepts, principles, and Java implementations for RESTful services. Today's development environments are increasingly dominated by sophisticated tooling that makes the implementation of RESTful services less arduous. The proper design of these services is far more complex and demanding. Java RESTful Service Essentials focuses on providing an understanding of the fundamental principles and technologies that are used in building these services. This understanding is critical to being able to diagnose, troubleshoot, tune, and perform other lifecycle activities. Session: Working with REST Overview of REST Designing RESTful Services JAX-RS Lesson: Introduction to JAX-RS @Path: URI Matching JAX-RS Content Negotiation JAX-RS Request and Response JAX-RS Client API JAX-RS Filters and Interceptors Asynchronous JAX-RS Additional course details: Nexus Humans Java REST Essentials (TT7305) 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 Java REST Essentials (TT7305) 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.

Build successful and effective multi-cultural teams with our practical, bespoke training courses. Help team members to embrace and harness the skills and abilities their different ages, nationalities, generations and life experiences bring. Courses include: Knowing your team Communication styles Communicative competency in multi-cultural teams Cultural intelligence – understanding our strengths A global mindset Breaking down barriers for better team working Experiential learning – a session in a second language Team dynamics

Duration 48.125 Days 288.75 CPD hours Cisco Learning Library: Collaboration provides on-demand training to help your IT staff design, implement, manage, and troubleshoot your organization?s collaboration and video infrastructure based on Cisco collaboration and unified communications solutions.This comprehensive technical training library includes full-length interactive certification courses, product and technology courses with labs, and thousands of reference materials. Collaboration Library Certification Courses CCNP Collaboration Implementing Cisco Collaboration Core Technologies (CLCOR) v1.0 Implementing Cisco Collaboration Applications (CLICA) v1.0 Implementing Cisco Advanced Call Control and Mobility Services (CLACCM) v1.0 Implementing Cisco Collaboration Cloud and Edge Solutions (CLCEI) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 CCIE Collaboration Implementing Cisco Collaboration Core Technologies (CLCOR) v1.0 Product and technology training Cisco Video Infrastructure Design (VID) v1.0 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 Implementing Cisco Advanced Call Control and Mobility Services (CLACCM) v1.0 Implementing Cisco Collaboration Applications (CLICA) v1.0 Implementing Cisco Collaboration Cloud and Edge Solutions (CLCEI) v1.0 Implementing Cisco Collaboration Core Technologies (CLCOR) v1.0 Understanding Cisco Collaboration Foundations (CLFNDU) v1.0

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 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 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 69 Days 414 CPD hours Cisco Learning Library: Security offers a subscription to all Cisco online cybersecurity and cyber operations training, including extensive sk This comprehensive technical training library offers full-length, interactive certification courses, product and technology training with labs, and thousands of reference materials. Security Library Certification Courses CCNP Security Implementing and Operating Cisco Security Core Technologies (SCOR) v1.0 Securing Networks with Cisco Firepower Next Generation Firewall (SSNGFW) v1.0 Securing Networks with Cisco Firepower Next-Generation IPS (SSFIPS) v4.0 Implementing and Configuring Cisco Identity Services Engine (SISE) v3.0 Securing Email with Cisco Email Security Appliance (SESA) v3.0 Securing the Web with Cisco Web Security Appliance (SWSA) v3.0 Implementing Secure Solutions with Virtual Private Networks (SVPN) v1.0 Implementing Automation for Cisco Security Solutions (SAUI) v1.0 CCIE Security Implementing and Operating Cisco Security Core Technologies (SCOR) v1.0 Product and Technology Training Implementing and Operating Cisco Security Core Technologies (SCOR) v1.0 Implementing Automation for Cisco Security Solutions (SAUI) v1.0 Understanding Cisco Cybersecurity Fundamentals (SECFND) v1.0 Implementing Cisco Cybersecurity Operations (SECOPS) v1.0 Implementing Secure Solutions with Virtual Private Networks (SVPN) v1.0 Implementing an Integrated Threat Defense Solution (SECUR201) v1.0 Integrated Threat Defense Investigation and Mitigation (SECUR202) v1.0 Securing Cisco Networks with Snort Rule Writing Best Practices (SSFRules) v2.0 Securing Cisco Networks with Open Source Snort (SSFSNORT) v3.0 Securing Networks with Cisco Firepower Next Generation Firewall (SSNGFW) v1.0 Securing Email with Cisco Email Security Appliance (SESA) v3.0 Securing the Web with Cisco Web Security Appliance (SWSA) v3.0 Securing Networks with Cisco Firepower Next-Generation IPS (SSFIPS) v4.0 Introduction to 802.1X Operations for Cisco Security Professionals (802.1X) v2.0 Securing Industrial IoT Networks with Cisco Technologies (ISECIN) v1.0 Implementing and Configuring Cisco Identity Services Engine (SISE) v3.0 Protecting Against Malware Threats with Cisco AMP for Endpoints (SSFAMP) v5.0 Introducing Cisco Cloud Consumer Security (SECICC) v1.0 Securing Cloud Deployments with Cisco Technologies (SECCLD) v1.0 Configuring Cisco ISE Essentials for SD-Access (ISESDA) v1.0 Securing Branch Internet and Cloud Access with Cisco SD-WAN (A-SDW-BRSEC)

Equality is everyone’s right and everyone’s responsibility’. This training promotes the requirements of the Equality and Diversity Act. This session will strengthen understanding of Equality & Diversity.

Duration 4.125 Days 24.75 CPD hours This course is intended for The job roles best suited to the material in this course are: Managers or consultants involved in Environmental Management, Expert advisors seeking to master the implementation of an Environmental Management System, Individuals responsible for maintaining conformance with EMS requirements , EMS team members Overview Acknowledge the correlation between ISO 14001, ISO 14040 and other standards and regulatory frameworks Master the concepts, approaches, methods and techniques used for the implementation and effective management of an EMS Learn how to interpret the ISO 14001 requirements in the specific context of an organization Learn how to support an organization to effectively plan, implement, manage, monitor and maintain an EMS Acquire the expertise to advise an organization in implementing Environmental Management System best practices ISO 14001 Lead Implementer training enables you to develop the necessary expertise to support an organization in establishing, implementing, managing and maintaining an Environmental Management System (EMS) based on ISO 14001. During this training course, you will also gain a thorough understanding of the best practices of Environmental Management Systems, consequently reducing an organization?s negative environmental impacts and improving its overall performance and efficiency Introduction to ISO 14001 and initiation of an EMS Course objective and structure Standard and regulatory framework Environmental Management System (EMS) Fundamental principles of environmental management Initiating the EMS implementation Understanding the organization and clarifying the environmental objectives Analysis of the existing management system Plan the implementation of the EMS Leadership and approval of the EMS project EMS scope Policies for environmental management Risk assessment Definition of the organizational structure of environmental management Implementation of an EMS Definition of the document management process Design of controls and drafting of specific policies & procedures Communication plan Training and awareness plan Implementation of controls Incident Management Operations Management EMS monitoring, measurement, continuous improvement and preparation for certification audit Monitoring, measurement, analysis and evaluation Internal audit Management review Treatment of problems and non-conformities Continual improvement Preparing for the certification audit Competence and evaluation of implementers Closing the training

Duration 4 Days 24 CPD hours This course is intended for Database Administrators Administrator Overview Describe the Oracle Clusterware architecture Describe how Grid Plug and Play affects Clusterware Describe the benefits of Oracle RAC Explain the necessity of global resources Describe global cache coordination Install the Oracle database software Create a cluster database Perform post-database-creation tasks Convert a single-instance Oracle database to RACs Explain the principles and purposes of clusters Define redo log files in a RAC environment Define undo tablespaces in a RAC environment Start and stop RAC databases and instances Modify initialization parameters in a RAC environment Configure the RAC database to use ARCHIVELOG mode and the fast recovery area Configure RMAN for the RAC environment This Oracle Database 12c: RAC Administration training will teach you about Oracle RAC database architecture. Expert Oracle University instructors will deep dive into Global Resources and Cache Fusion. This Oracle Database 12c: RAC Administration training will teach you about Oracle RAC database architecture. Expert Oracle University instructors will deep dive into Global Resources and Cache Fusion. Additional course details: Nexus Humans Oracle Database 12c - RAC Administration 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 Oracle Database 12c - RAC Administration 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.