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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 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 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)

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: A technical audience at an intermediate level Overview Using Amazon SageMaker, this course teaches you how to: Prepare a dataset for training. Train and evaluate a machine learning model. Automatically tune a machine learning model. Prepare a machine learning model for production. Think critically about machine learning model results In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment. Day 1 Business problem: Churn prediction Load and display the dataset Assess features and determine which Amazon SageMaker algorithm to use Use Amazon Sagemaker to train, evaluate, and automatically tune the model Deploy the model Assess relative cost of errors Additional course details: Nexus Humans Practical Data Science with Amazon SageMaker 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 Practical Data Science with Amazon SageMaker 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 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.

Duration 3 Days 18 CPD hours This course is intended for Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek an understanding of the parallel framework architecture. In this course, students will develop a deeper understanding of the DataStage architecture, including a deeper understanding of the DataStage development and runtime environments. Introduction to the Parallel Framework Architecture Describe the parallel processing architecture Describe pipeline and partition parallelism Describe the role of the configuration file Design a job that creates robust test data Compiling & Executing Jobs Describe the main parts of the configuration file Describe the compile process and the OSH that the compilation process generates Describe the role and the main parts of the Score Describe the job execution process Partitioning & Collecting Data Understand how partitioning works in the Framework Viewing partitioners in the Score Selecting partitioning algorithms Generate sequences of numbers (surrogate keys) in a partitioned, parallel environment Sorting Data Sort data in the parallel framework Find inserted sorts in the Score Reduce the number of inserted sorts Optimize Fork-Join jobs Use Sort stages to determine the last row in a group Describe sort key and partitioner key logic in the parallel framework Buffering in Parallel Jobs Describe how buffering works in parallel jobs Tune buffers in parallel jobs Avoid buffer contentions Parallel Framework Data Types Describe virtual data sets Describe schemas Describe data type mappings and conversions Describe how external data is processed Handle nulls Work with complex data Reusable Components Create a schema file Read a sequential file using a schema Describe Runtime Column Propagation (RCP) Enable and disable RCP Create and use shared containers Balanced Optimization Enable Balanced Optimization functionality in Designer Describe the Balanced Optimization workflow List the different Balanced Optimization options. Push stage processing to a data source Push stage processing to a data target Optimize a job accessing Hadoop HDFS file system Understand the limitations of Balanced Optimizations Additional course details: Nexus Humans KM404 IBM InfoSphere Advanced DataStage - Parallel Framework (v11.5) 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 KM404 IBM InfoSphere Advanced DataStage - Parallel Framework (v11.5) 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.

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Effective communication in the workplace is part and parcel of our daily lives, but not everyone is a natural.  Do you find it tough standing up in front of people? Does the thought of engaging with audiences in any setting fill you with anxiety? Is doing a remote video message to colleagues on Zoom or Teams a tough call? Do you do it regularly but need some professional guidance on whether it’s working? At CoComms we can improve every aspect of your performance and offer a range of tips and techniques to help manage these environments and keep your audience engaged and interested. Public Speaking and Presentation Training In a professional setting it’s vital to come across as dynamic, trustworthy, credible and real. You want people to trust you and in turn get behind your vision or plan or proposal. If you can achieve this you can improve your confidence, your engagement and your prospects. Our training is designed to hone your presentation skills so whether you are pitching for work, taking colleagues through change or speaking to a new audience, you can do it with a clarity and confidence that makes your messages clear and insightful. The training includes: Perfecting your slides Working to produce a clean, easy to navigate slide deck that give logic and flow to your presentation. Developing your storytelling We use our journalistic techniques to show you how to build a story to keep your audience engaged with a well-structured and entertaining presentation. Calls to Action Make sure it is clear what you want to achieve and what you want from your audience. Rehearse and Review We film and then playback a range of practical presentation exercises so we can review your performance and work to make any improvements. Conference and Panel Training The audience at a conference may be a captive one, but that doesn’t mean they are always listening and engaging with what you have to say. We can make sure your keynote speech or panel contribution is memorable, appreciated by your audience and beneficial to your business. Our training looks at preparing for and delivering a speech from start to finish and includes: Defining your big ideas What is it you want to say and what do you want your audience to remember? Develop your narrative and script How can you get across your message using storytelling. Choosing the right language How vibrant and energised language can make the difference in your speech. The tips and tricks to make sure your speech is memorable How vocabulary and delivery techniques ensure your words are heard. Controlling the message How to deal with unhelpful questions and return to the main aspects of your story. Stakeholder Communication Training Engaging effectively with stakeholders with clarity and confidence can make all the difference to your relationships. A successful “town hall” meeting can win over your sceptics, convince those who are unsure and build a common goal between your business and stakeholders. Our stakeholder communication training prepares you for these vital meetings and includes: Focusing the meeting We look at how to control the meeting so the important business is covered and how to prepare for any questions or comments you may receive. Keep control of the conversation We teach you conversational techniques to focus on the main points without being too assertive or dismissive. Rehearse and Review We use video and practical role-play exercises to assess your performance and look for ways to improve. Breaking down the information We look at how to present facts and figures without overwhelming (or boring!) your audience. Our techniques will help you narrate the message in a clear and comprehensive way. Making an impact Using our journalistic experience we will work with you to develop your presentation skills to make the biggest impact and demonstrate credibility and authority. Video Calls for Business The world has changed. Now is the time to ensure your business is changing too. Many in-person meetings, conferences, networking events and clients hosting are, for now, a thing of the past. These face-to-face interactions have been replaced by video calls, webinars and online events. So, how do you develop contacts, maintain relationships and manage your team in this new virtual world? How do you look and sound confident, be heard, and build trust and credibility through a computer screen? At CoComms, we are online communications experts and our years of experience in broadcasting mean we understand how to engage a virtual audience. Interactive and practical training We work with you through a variety of scenarios to analyse your performance on video calls. Feedback on your performance We offer supportive, positive feedback and share our tried and tested techniques so you can improve. Make Video Calls work for you Through our training you will become more confident, more productive and more dynamic on video calls. Contact us If you have a query regarding any of our services or would like to book a consultation for free initial advice and guidance please get in touch