24 Hours Left! Don't Let Year-End Deals Slip Away - Enrol Now! Food safety training is required for a wide range of employment in a wide range of sectors. Workers, from those directly involved in food production to those who sell it at retail, must learn how to operate safely with food meant for consumption. This is where HACCP Food Safety comes in. HACCP (Hazard Analysis Critical Control Points) is a globally recognised method for identifying and controlling food safety. As a result, we provide the HACCP Food Safety at QLS Level 5 course to help you learn important information and get a head start in the linked business. Learners will obtain a thorough grasp of food hygiene best practices in this extensive HACCP Food Safety course, ensuring that their firm receives a five-star exceptional national hygiene food rating. You will learn how to keep foods hazard-free. You will also comprehend the core concepts of hazard analysis and control points. This course will even help you improve your personal hygiene. You will also receive specialised lessons on HACCP and food premises. It is legally needed to know and understand the foundations of food safety and hygiene in order to avoid contaminating food and to always be safe at work. This course provides up-to-date knowledge on food hygiene through a range of lessons to ensure that you have a thorough awareness of your duties surrounding food safety and HACCP. So, what are you waiting for? Enrol Right Now! Learning Outcomes Upon successful completion of this HACCP Food Safety at QLS Level 5 course, you will be able to: Learn all there is to know about the HACCP system and food safety regulations. Learn about the many sorts of food safety hazards and how to avoid them. Determine the actions required to create and implement the HACCP system. Acquire a deep grasp of critical control points. Understand the HACCP criteria and how to begin using your HACCP system. Experts created the course to provide a rich and in-depth training experience for all students who enrol in it. Enrol in the course right now and you'll have immediate access to all of the HACCP Food Safety course materials. Then, from any internet-enabled device, access the course materials and learn when it's convenient for you. Start your learning journey straight away with this course and take a step toward a brighter future! Why Prefer this Course? Opportunity to earn a certificate endorsed by the Quality Licence Scheme and another certificate accredited by CPD after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery) Standard-aligned lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete the program in your own time, at your own pace Each of our students gets full 24/7 tutor support *** Course Curriculum *** Here is the curriculum breakdown of the course: Module 01: Introduction Module 02: HACCP and Food Safety Legislation Module 03: Food Safety Hazards Module 04: Planning a HACCP System Module 05: Creating the System Module 06: Principle 1: Hazard Analysis Module 07: Principle 2: Critical Control Points Module 08: Principle 3: Critical Limits Module 09: Principle 4: Monitoring Critical Control Points Module 10: Principle 5: Corrective Action Module 11: Principle 6: Verification of the System Module 12: Principle 7: Documentation Module 13: Implementing the System Module 14: Alternatives Assessment Process We offer an integrated assessment framework to make the process of evaluation for learners easier. After completing an online module, you will be given immediate access to a specially designed MCQ test. The results will be immediately analyzed, and the score will be shown for your review. The passing score for each test will be set at 60%. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you have completed all of the exams. CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Course Right for You? Food industry professionals Quality control and assurance personnel Food safety supervisors, managers, or auditors Individuals aspiring to work in the food industry Entrepreneurs or business owners in the food sector Requirements The HACCP Food Safety program does not require any prior knowledge; everyone may participate! This HACCP Food Safety course is open to anyone interested in learning from anywhere in the world. This 100% online course can be accessed from any internet-connected device, such as a computer, tablet, or smartphone. Career path HACCP Food Safety at QLS Level 5 course is a helpful certificate to have. It is advantageous for many professions, including: Quality Supervisor Hygiene Manager Food Safety Advisor Hotel and Restaurant Service Staff In the UK, these professions earn an average salary of £22,000 - £60,000 per annum. Certificates Level 5 QLS Endorsed Certificate Hard copy certificate - Included CPD Accredited Certificate Digital certificate - £10
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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 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 5 Days 30 CPD hours This course is intended for System architects and system administrators Overview By the end of the course, you should be able to meet the following objectives: Introduce troubleshooting principles and procedures Use command-line interfaces, log files, and the vSphere Client to diagnose and resolve problems in the vSphere environment Explain the purpose of common vSphere log files Identify networking issues based on reported symptoms Validate and troubleshoot the reported networking issue Identify the root cause of networking issue Implement the appropriate resolution to recover from networking problems Analyze storage failure scenarios using a logical troubleshooting methodology identify the root cause of storage failure Apply the appropriate resolution to resolve storage failure problems Troubleshoot vSphere cluster failure scenarios Analyze possible vSphere cluster failure causes Diagnose common VMware vSphere High Availability problems and provide solutions Identify and validate VMware ESXiTM host and VMware vCenter problems Analyze failure scenarios of ESXi host and vCenter problems Select the correct resolution for the failure of ESXi host and vCenter problems Troubleshoot virtual machine problems, including migration problems, snapshot problems, and connection problems Troubleshoot performance problems with vSphere components This five-day training course provides you with the knowledge, skills, and abilities to achieve competence in troubleshooting the VMware vSphere© 8 environment. This course increases your skill level and competence in using the command-line interface, VMware vSphere© Client?, log files, and other tools to analyze and solve problems. 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 troubleshooting methodology to logically diagnose faults and improve troubleshooting efficiency Troubleshooting Tools Discuss the various methods to run commands Discuss the various ways to access ESXi Shell Use commands to view, configure, and manage your vSphere components Use the vSphere CLI Use ESXCLI commands from the vSphere CLI Use Data Center CLI commands Identify the best tool for command-line interface troubleshooting Identify important log files for troubleshooting vCenter Server and ESXi Describe the benefits and capabilities of VMware SkylineTM Explain how VMware Skyline works Describe VMware SkylineTM Health Describe VMware Skyline AdvisorTM Troubleshooting Virtual Networking Analyze and troubleshoot standard switch problems Analyze and troubleshoot virtual machine connectivity problems Analyze and troubleshoot management network problems Analyze and troubleshoot distributed switch problems Troubleshooting Storage Discuss the vSphere storage architecture Identify the possible causes of problems in the various types of datastores Analyze the common storage connectivity and configuration problems Discuss the possible storage problems causes Solve the storage connectivity problems, correct misconfigurations, and restore LUN visibility Review vSphere storage architecture and functionality necessary to troubleshoot storage problems Use ESXi and Linux commands to troubleshoot storage problems Analyze log file entries to identify the root cause of storage problems Investigate ESXi storage issues Troubleshoot VM snapshots Troubleshoot storage performance problems Review multipathing Identify the common causes of missing paths, including PDL and APD conditions Solve the missing path problems between hosts and storage devices Troubleshooting vSphere Clusters Identify and troubleshoot vSphere HA problems Analyze and solve vSphere vMotion problems Diagnose and troubleshoot common vSphere DRS problems Troubleshooting Virtual Machines Discuss virtual machine files and disk content IDs Identify, analyze, and solve virtual machine snapshot problems Troubleshoot virtual machine power-on problems Identify possible causes and troubleshoot virtual machine connection state problems Diagnose and recover from VMware Tools installation failures Troubleshooting vCenter Server and ESXi Analyze and solve vCenter Server service problems Diagnose and troubleshoot vCenter Server database problems Use vCenter Server Appliance shell and the Bash shell to identify and solve problems Identify and troubleshoot ESXi host problems
Learn how to implement EC2 and VPC resources on AWS using the Python API: Boto3! Implement your infrastructure with code!