3353 Design courses in Driffield delivered Live Online

Join our Home Office Audit course to gain the expertise needed to navigate Home Office compliance and audit visits successfully. Prepare your organisation for compliance excellence with our comprehensive training Contact our legal team for more information and to learn more about our immigration training courses. Our Home Office Audit Training is designed to empower HR professionals, employers, and businesses with the knowledge and skills necessary to confidently handle compliance checks and excel during audit visits. Whether you’re new to compliance or looking to enhance your organization’s audit readiness, this comprehensive course covers the full spectrum of Home Office audits. From identifying triggers for compliance checks to post-audit follow-up and consequences, we provide practical insights and strategies for success. By the end of this training, you will be well-equipped to navigate Home Office compliance and enforcement visits with confidence. Gain the knowledge and practical skills necessary to ensure your organisation’s compliance, excel during audits, and effectively address any audit matters that may arise.   Course joining links, materials and instructions are sent out 24hours before the course starts. Why Study with Immigration Advice Service? Immigration Advice Service has been providing professional immigration services for over 10 years in the public, private and corporate sectors. Our fully qualified and OISC regulated trainer will guide you through the process and ensure you are competent with elements covered within the course. Course Content: Overview of Home Office Compliance and enforcement visits Identifying triggers for compliance checks What the audit visit entails – format & scope Key focus for Home Office Audit Common questions asked at audit visit Practical tips to attend Post audit follow up and consequences

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Those who will provide container orchestration management in the AWS Cloud including: DevOps engineers Systems administrators Overview In this course, you will learn to: Review and examine containers, Kubernetes and Amazon EKS fundamentals and the impact of containers on workflows. Build an Amazon EKS cluster by selecting the correct compute resources to support worker nodes. Secure your environment with AWS Identity and Access Management (IAM) authentication by creating an Amazon EKS service role for your cluster Deploy an application on the cluster. Publish container images to ECR and secure access via IAM policy. Automate and deploy applications, examine automation tools and pipelines. Create a GitOps pipeline using WeaveFlux. Collect monitoring data through metrics, logs, tracing with AWS X-Ray and identify metrics for performance tuning. Review scenarios where bottlenecks require the best scaling approach using horizontal or vertical scaling. Assess the tradeoffs between efficiency, resiliency, and cost and impact for tuning one over the other. Describe and outline a holistic, iterative approach to optimizing your environment. Design for cost, efficiency, and resiliency. Configure the AWS networking services to support the cluster. Describe how EKS/Amazon Virtual Private Cloud (VPC) functions and simplifies inter-node communications. Describe the function of VPC Container Network Interface (CNI). Review the benefits of a service mesh. Upgrade your Kubernetes, Amazon EKS, and third party tools Amazon EKS makes it easy for you to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. In this course, you will learn container management and orchestration for Kubernetes using Amazon EKS. You will build an Amazon EKS cluster, configure the environment, deploy the cluster, and then add applications to your cluster. You will manage container images using Amazon Elastic Container Registry (ECR) and learn how to automate application deployment. You will deploy applications using CI/CD tools. You will learn how to monitor and scale your environment by using metrics, logging, tracing, and horizontal/vertical scaling. You will learn how to design and manage a large container environment by designing for efficiency, cost, and resiliency. You will configure AWS networking services to support the cluster and learn how to secure your Amazon EKS environment. Module 0: Course Introduction Course preparation activities and agenda Module 1: Container Fundamentals Best practices for building applications Container fundamentals Components of a container Module 2: Kubernetes Fundamentals Container orchestration Kubernetes objects Kubernetes internals Preparing for Lab 1: Deploying Kubernetes Pods Module 3: Amazon EKS Fundamentals Introduction to Amazon EKS Amazon EKS control plane Amazon EKS data plane Fundamentals of Amazon EKS security Amazon EKS API Module 4: Building an Amazon EKS Cluster Configuring your environment Creating an Amazon EKS cluster Demo: Configuring and deploying clusters in the AWS Management Console Working with eksctl Preparing for Lab 2: Building an Amazon EKS Cluster Module 5: Deploying Applications to Your Amazon EKS Cluster Configuring Amazon Elastic Container Registry (Amazon ECR) Demo: Configuring Amazon ECR Deploying applications with Helm Demo: Deploying applications with Helm Continuous deployment in Amazon EKS GitOps and Amazon EKS Preparing for Lab 3: Deploying App Module 6: Configuring Observability in Amazon EKS Configuring observability in an Amazon EKS cluster Collecting metrics Using metrics for automatic scaling Managing logs Application tracing in Amazon EKS Gaining and applying insight from observability Preparing for Lab 4: Monitoring Amazon EKS Module 7: Balancing Efficiency, Resilience, and Cost Optimization in Amazon EKS The high level overview Designing for resilience Designing for cost optimization Designing for efficiency Module 8: Managing Networking in Amazon EKS Review: Networking in AWS Communicating in Amazon EKS Managing your IP space Deploying a service mesh Preparing for Lab 5: Exploring Amazon EKS Communication Module 9: Managing Authentication and Authorization in Amazon EKS Understanding the AWS shared responsibility model Authentication and authorization Managing IAM and RBAC Demo: Customizing RBAC roles Managing pod permissions using RBAC service accounts Module 10: Implementing Secure Workflows Securing cluster endpoint access Improving the security of your workflows Improving host and network security Managing secrets Preparing for Lab 6: Securing Amazon EKS Module 11: Managing Upgrades in Amazon EKS Planning for an upgrade Upgrading your Kubernetes version Amazon EKS platform versions Additional course details: Nexus Humans Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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.

BOHS P903 - Management and control of evaporative cooling and other high risk industrial systems is there to provide background and an overview of the risk of Legionella infection and how it can be controlled in Evaporative Cooling and other high risk Industrial type systems. It is a requirement of this course that candidates have successfully completed P901 - Legionella- Management and Control of Building Hot and Cold Water Services. Where both P901 and P903 courses are run on subsequent days or as a combined course then this prerequisite is waived.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts 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. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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.

The LMI Foundations of Success workshop introduces the concepts and practical tools used to help countless individuals within thousands of organisations, of all sizes and complexity in both the public and private sector, realise more of their true potential.

Enhance your skills and learn how to use a range of advanced formulas and functions to manage and extract data more efficiently. There are some great ones here that will save a lot of time. Course overview Duration: 1 day (6.5 hours) Our Excel Module 4 – Advanced Formulas and Functions course looks at some of the more advanced functions of Excel that can be used to manipulate and extract data. This is an intensive one-day course and designed for experienced users of Excel. Participants should be confident in creating and using Excel and be able to build simple formula before attending. Objectives By the end of the course you will be able to: Use a range of Text functions to manage text data Create and use different types of date and time functions Work with rounding functions Use logical statements Build nested formula Use SUMIF, COUNTIF and AVERAGEIF Cross reference data from other worksheets using LOOKUP, INDEX and MATCH functions Use IS functions and IFERROR to test cell values Content Working with text Splitting text into multiple cells Merging data into one cell Extracting data using text functions Tidying data Working with dates and times Formatting dates and times Date and time functions Calculating date and time differences Using functions to round numbers up and down ROUND ROUNDUP ROUNDDOWN CEILING FLOOR Use lookup functions Lookup functions Creating a lookup table Range naming Using VLOOKUP Using HLOOKUP Using INDEX and MATCH Working with logical statements Creating an IF statement Using the AND plus OR functions Nesting functions Calculating values based on given criteria SUMIF(S) COUNTIF(S) AVERAGEIF(S) Using IS and IFERROR and test cell values ISBLANK ISNUMBER ISTEXT ISERROR IFERROR

Duration 1 Days 6 CPD hours This course is intended for Certification Preparation for Platform App Builder is ideal for administrators, system integrators, and independent software vendors (ISVs) with an interest in sharpening the development, deployment, and administrative skills required to succeed in becoming a Salesforce Certified Platform App Builder Overview Architect and manage the correct data model based on business requirements. Configure application security. Define business logic and process automation declaratively. Design user interfaces. Customize applications for mobile use and Lightning. Deploy applications. Are you ready to take the next step in your career by becoming a Salesforce Certified Platform App Builder? By covering the details around the exam objectives, this course will help hone your knowledge of Salesforce application lifecycle management and the declarative and programmatic solutions available to you through guided scenarios, lecture, and discussion. Salesforce Fundamentals Capabilities of core CRM objects Boundaries of declarative customizations Use cases for programmatic customizations Security Restricting and extending object, record, and field access Determining appropriate sharing solutions Data Modeling and Management Determining an appropriate data model Relationship types and impact on record access, user interface, and reporting Considerations for changing field types Considerations of the schema builder Considerations for importing and exporting data Use cases of external objects Reporting Creating reports Report types Dashboards User Interface Customization options Custom buttons, links, and actions Declarative options for incorporating Lightning Components Mobile Declarative customizations available for the Salesforce1 user interface Business Logic and Process Automation Record types Formula fields Roll-up summary fields Validation rules Approval processes Workflow Visual workflow Process builder Automating business processes Ramifications of field updates and potential for recursion App Deployment Application lifecycle Sandboxes Change sets Unmanaged and managed packages Determining an appropriate deployment plan Wrapping Up Test preparation Practice exam

Course Overview: The "Shading in Adobe Photoshop" course is designed to introduce learners to the art and techniques of shading within Adobe Photoshop. This course covers essential tools and methods for creating realistic lighting effects, depth, and texture in digital artwork. Learners will explore various shading techniques, including the use of brushes, gradients, and layer blending modes. The course is aimed at enhancing skills in digital illustration and photo manipulation, offering a comprehensive understanding of how to use shading to add dimension and realism to designs. By the end of the course, learners will have the skills to apply these techniques to create polished and professional-level artwork. Course Description: This course dives deeper into the various shading techniques in Adobe Photoshop, equipping learners with the knowledge to enhance their digital creations. Topics include using custom brushes for shading, adjusting opacity levels, working with gradients to simulate light, and mastering layer blending modes for depth. The course also covers how to apply shading effectively across different types of artwork, such as illustrations, portraits, and product designs. Learners will gain the ability to create smooth transitions, realistic highlights, and shadows to elevate their designs. The course encourages creativity while ensuring that students develop the technical expertise needed to implement these techniques in a professional setting. Course Modules: Module 01: Introduction to Shading in Photoshop Module 02: Understanding Light and Shadow Module 03: Using Brushes for Shading Module 04: Gradient Techniques for Shading Module 05: Layering and Blending Modes Module 06: Creating Depth and Realism in Artwork Module 07: Shading for Various Art Styles (See full curriculum) Who is this course for? Individuals seeking to improve their digital art skills. Professionals aiming to enhance their graphic design portfolio. Beginners with an interest in digital illustration and design. Artists looking to expand their Photoshop capabilities. Career Path Graphic Designer Digital Illustrator Photo Manipulation Artist Concept Artist Visual Designer

This workshop is designed to give those who have to give bad news and broach difficult conversations increased confidence. Participants will leave the workshop with the tools and techniques to prepare for a difficult conversation and ensure that they are supporting patients and relatives through a stressful time in their lives.

This qualification is designed for Water Network Field Managers, Operational Managers, Project Managers, Department Heads, and other practising Senior and Middle Managers. The qualification will develop your technical skills and understanding of the Management of demand Management & Leakage and improve your performance. It will encourage strategic thinking at this level of management to foster business improvement. Main themes Understand the role demand management plays in the water industry sustainability plan Understand the range of demand management tools available and their effectiveness Understand the application of leakage strategies, the economic value and the external influences Understand data handling, meaningful leakage calculations and the interpretation of leakage data Understand various leakage control methods used and their respective effectiveness and economic cost-benefit Understand network repair and maintenance methods and the provision of these services Instructions This online course will be delivered using CISCO Webex. You will need a suitable device with a camera and microphone like a laptop. If you have any questions about what is required, please contact us on enquiries@learninganddevelopment.associates. Qualification All learners taking the qualification will need to produce identification to enable ProQual registration. This can take the form of a: Passport Driving Licence Construction Skills Certification Scheme Card (CSCS Card) Construction Plant Competence Scheme Card (CPCS Card) If none of the above are available to the learner, a photograph with a statement confirming their identity, dated and signed, along with a utility bill, would be acceptable.