3327 Design courses in Colchester delivered Live Online

Second Degree Usui Reiki Course You will be taught how to conduct a healing session; protocols, etc and how to perform distance healings. This course is comprehensive and detailed. You will have all the tools you need to start using Reiki on others and their pets. Upon completion of this comprehensive and insightful Reiki course, you can go on to get insurance to set up as a Reiki Practitioner and start seeing clients.

3 x Online Women's Voice Medicine SessionsThe Journey to Vocal Freedom "Our Voices are like seeds, they can sit dormant until the right conditions present themselves, and when this occurs they come bursting out full bloom!"These sessions are designed as a ritual. We have a consultation at first to determine what to energetically work on and to set intentions. I then guide you through your own Voice Empowerment Journey, we use meditation, affirmations, embodied movement, breathwork and playful sounding to support your journey to a fuller, confident and expressive voice.  Things I can support you with: Learning how to trust your Voice How to feel more confident in your own self expression Finding creativity in your flow Understanding how to use your voice for healing How to work with both the Shakti and Shiva energies in sound Finding love for your own authentic Voice and Sound The 3 week online 1-1 Voice Medicine sessions will support you to go deeper into your journey with embodying your voice as a healing tool. This will involve dropping into a new exploration each week: Week 1: Voice Play - Activating the Inner Child Week 2: Voice Power - Learning how to expand your sound Week 3: Voice and Emotion - Explore how to transmute your emotion into embodied sound If you are a practising sound healer, we can also work on how you can open your voice as a healing tool to support your sound healing journeys.This 3 week 1-1 Voice Medicine Journey costs £250.  "The journey to vocal freedom is a beautiful one, and is becoming more important for us women as the Feminine energies continue to rise."If you are feeling ready to unleash your inner Goddess through sacred sound, then I would be honoured to support you.

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.

Anatomy and physiology

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.

Reboot Your Brain for Success & Peak Performance is a Neuroencoding Method that delivers long lasting results. The complete program walks participants through the five elements it takes to clear out their brain, boost up their mindset, and update their mental faculties. This workshop is perfect for anyone who wants to reset to their magnificent default.

Learn how to use Macros in Excel to automate your work and start to see the power these can give you. Course overview Duration: 1 day (6.5 hours) Our Excel – Working with Macros course aims to show how macros can be used to automate commonly used commands and processes. This course is designed for existing experienced users of Excel. You should be confident creating and manipulating Excel spreadsheets and creating formulas before attending this course. Objectives By the end of the course you will be able to: Record and run macros Navigate within the Visual Basic Environment Edit pre-recorded macros Create your own functions Content Recording macros Accessing the Developer Tab Naming conventions and storage locations Recording macros Absolute and relative cell addressing Running macros Assigning macros to the Quick Access Toolbar Assigning macros to objects Creating new tabs Workbook macros Recording macros in a specific workbook Saving the workbook as an Excel Macro-Enabled Workbook Creating quick access items specific to workbooks Importing and manipulating data Importing Delimited Text Files Importing Fixed Width Text Files The Visual Basic environment Project explorer Code window Properties window Renaming modules Deleting modules Working with code Code structure Adding comments Navigating within your code Editing macro code Getting help with syntax Debugging Errors Using debug Function procedures Creating function macros

An in depth look at Pivot Tables and their powerful features to summarise and visualize your data. Course overview Duration: 1 day (6.5 hours) Our Excel – Pivot Table Specialist course is a comprehensive guide to working with Pivot Tables for those who need to learn more about the use of Pivot Tables to summarise and analyse information. This course is designed for existing experienced users of Excel. You should be a confident Excel user and be able to create and edit worksheets and write basic formulas. Objectives By the end of the course you will be able to: Build and customise Pivot Tables Group and sort information Filter information Use slicers and the timeline filter Add different summary calculations Create Pivot Charts Add calculated fields and items Content The anatomy of a Pivot Table Using a Pivot Cache Building a Pivot Table The Pivot Table interface Refreshing the Pivot Table Adding column, row, page and data fields Changing data orientation Showing data fields in columns or rows Drilling down to underlying data Setting Pivot Table options Format options Totals and filters options Display and printing options Data options Customising Pivot Tables Modifying field names Data formatting Changing field layout options Changing summary calculations Working with subtotals Filtering and sorting Filtering items Sorting data Value and label filters Creating top 10 reports Using the Search filter Using the Slicer tool Use the Timeline filter Grouping Grouping date fields Grouping numeric fields Adding your own groups Summary calculations Running totals Differences year on year, month on month % Differences year on year, month on month % of Row, Column, Total and other fields Pivot charts Pivot Chart rules Creating a Pivot Chart Working with your Pivot Chart Creating calculations Adding calculated fields Adding calculated items

Join us on Thu Nov 07 2024 at 10:00:00 GMT for an exciting online event focused on enhancing your leadership skills. Whether you are an established leader or just starting out, this session is designed to boost your confidence and help you lead with clarity and purpose.

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