39946 Courses

The Menopause Support Coach Certification is a dual certified and doubly accredited CPD and ActiveiQ online course.  A 3 month program that trains students to be compassionate, alert to & effective in menopause support and to become a world class MSCC level coach.  This is fully delivered online via a learning portal with private log in and is for anyone ... Working with and supporting women in their life business, career and happiness journey e.g. health & fitness coaches, PTs, Life Coaches, Business Coaches, Mindset Coaches, Women’s Health Coaches You want to deepen your knowledge of the menopause and women’s health space to offer a new level of support in your coaching You want to become part of a community of like-minded people and open up new exciting opportunities for yourself You want to make a long lasting impact on the world in a big and positive way You’ll learn: – Menopause well-being nutrition to understanding your clients better, – How to coach menopausal clients towards their goals, – How to hold space for where they are right now, – The basics of HRT (Hormone Replacement Therapy) to be able to guide your clients through their journey safely and successfully. Not only that but It’s going to open up new and exciting opportunities in a growing industry of women’s health, as well as equip you as a coach in this space to enable your business to expand or niche. Sign Up to the waitlist for further details on the next cohort intake by contacting support@adelejohnstoncoaching.com.  Please note this is a paid for certification with BONUSES and discounts for waitlist members. This is not a free course.

Learners develop an essential understanding of caring for people with dementia, and covers the benefits of positive communication, use of medication, and importance of highly individualised, person-centred care

leadership management training course

Duration 5 Days 30 CPD hours This course is intended for Operators, administrators, and architects responsible for the creation, maintenance, or delivery of remote and virtual desktop services. Overview By the end of the course, you should be able to meet the following objectives: Recognize the features and benefits of Horizon Use VMware vSphere to create VMs to be used as desktops for Horizon Create and optimize Windows VMs to create Horizon desktops Install and configure Horizon Agent on Horizon desktop Configure and manage the VMware Horizon Client™ systems and connect the client to a VMware Horizon desktop Configure, manage, and entitle desktop pools of full VMs Configure, manage, and entitle pools of instant-clone desktops Create and use Remote Desktop Services (RDS) desktops and application pools Monitor the Horizon environment using Horizon Console Dashboard and Horizon Help Desk Tool Implement a structured approach to troubleshooting Resolve common issues that occur in a Horizon environment Troubleshoot issues with linked and instant clones Configure the Windows client Identify the correct log level for gathering logs Optimize protocols for the best end-user experience VMware Horizon© 8: Virtual Desktop Bootcamp is a five-day combination course of VMware Horizon 8: Skills for Virtual Desktop Management and VMware Horizon 8: Virtual Desktop Troubleshooting. This training combination gives you the skills to deliver virtual desktops and applications through a single virtual desktop infrastructure platform. You build skills in configuring and managing VMware Horizon 8 through a combination of lecture and hands-on labs. You learn how to configure and deploy pools of virtual machines and how to provide a customized desktop environment to end-users. Additionally, you learn how to resolve common issues that occur in a VMware Horizon environment. You engage in a series of lab exercises to bring existing environment issues to resolution. The exercises mirror real-world troubleshooting use cases. These exercises equip learners with the knowledge and practical skills to manage typical challenges faced by virtual desktop administrators and operators. Course Introduction Introductions and course logistics Course objectives Introduction to VMware Horizon Recognize the features and benefits of VMware Horizon Describe the conceptual and logical architecture of VMware Horizon Introduction to Use Case Define a use case for your virtual desktop and application infrastructure Convert customer requirements to use-case attributes vSphere for Horizon 8 Explain basic virtualization concepts Use VMware vSphere© Client? to access your vCenter Server system and VMware ESXi? hosts Create, provision, and remove a virtual machine VMware Horizon Desktops Create a Windows and a Linux virtual machine using vSphere Optimize and prepare Windows and Linux virtual machines to set up VMware Horizon desktop VMs VMware Horizon Agents Outline the configuration choices when installing Horizon Agent on Windows and Linux virtual machines Create a gold master for Windows Horizon desktops VMware Horizon Pools Identify the steps to set up a template for desktop pool deployment List the steps to add desktops to the VMware Horizon© Connection Server? inventory Compare dedicated-assignment and floatingassignment pools Outline the steps to create an automated pool Define user entitlement Explain the hierarchy of global, pool-level, and userlevel policies VMware Horizon Client Options Describe the different clients and their benefits Access Horizon desktop using various Horizon clients and HTML Configure integrated printing, USB redirection, and the shared folders option Configure session collaboration and media optimization for Microsoft Teams Creating and Managing Instant-Clone Desktop Pools List the advantages of instant clones Explain the provisioning technology used for instant-clone desktop pools Set up an automated pool of instant clones Push updated images to instant-clone desktop pools Creating RDS Desktop and Application Pools Explain the difference between an RDS desktop pool and an automated pool Compare and contrast an RDS session host pool, a farm, and an application pool Create an RDS desktop pool and an application ool Access RDS desktops and application from Horizon Client Use the instant clone technology to automate the build-out of RDSH farms Configure load-balancing for RDSHs on a farm Monitoring VMware Horizon Monitor the status of the VMware Horizon components using the Horizon Administrator console dashboard Monitor desktop sessions using the HelpDesk tool Overview of Virtual Desktop Troubleshooting Structured approach to troubleshooting configuration and operational problems Applying troubleshooting methods

Duration 2 Days 12 CPD hours This course is intended for vSphere administrators, architects, system engineers, and systems integrators who are responsible for the deployment or management of Site Recovery Manager Overview By the end of the course, you should be able to meet the following objectives: Summarize the components of Site Recovery Manager architecture Deploy and configure the Site Recovery Manager appliance Describe the principal disaster recovery topologies that are used with Site Recovery Manager Configure inventory and resource mappings Describe the storage replication options that are used with Site Recovery Manager Configure Site Recovery Manager to leverage array-based replication Describe VMware vSphere Replication™ functionality Describe the vSphere Replication architecture Deploy and configure vSphere Replication for use with Site Recovery Manager Build Site Recovery Manager protection groups based on vSphere Replication Build, edit, execute, test, and remove a recovery plan Perform a planned migration Perform reprotect and failback using Site Recovery Manager and vSphere Replication This hands-on training course gives experienced VMware vSphere© administrators the knowledge to install, configure, and manage VMware Site Recovery Manager? 8.2. This course also shows you how to write and test disaster recovery plans that use Site Recovery Manager. Course Introduction Outline the necessary information to effectively undertake this course Identify resources for additional information Overview and Architecture Discuss Site Recovery Manager architecture Examine disaster recovery options with Site Recovery Manager Describe Site Recovery Manager integration with VMware vSphere© ClientTM Discuss Site Recovery Manager features Analyze Site Recovery Manager storage policies and integration options Discuss how Site Recovery Manager supports several disaster recovery topologies identify use cases for Site Recovery Manager across various scenarios Describe how VMware Site Recovery? for VMware Cloud? on AWS integrates with Site Recovery Manager. Deploy & Configure Site Recovery Manager Identify the requirements to deploy Site Recovery Manager Discuss the benefits of the Site Recovery Manager appliance Explore vSphere deployment models Deploy the Site Recovery Manager appliance Navigate the Site Recovery Manager configuration user interface Describe the process to register Site Recovery Manager with VMware vCenter Server© Configure site pairing Identify how to perform updates to the Site Recovery Manager appliance Configuring Inventory Mappings Outline the importance of inventory mappings Examine configuration options for inventory mappings Outline the importance of placeholders Using Array-based Replication Describe array-based replication Discuss the role of the Storage Replication Adapter (SRA) Explore the relationship between devices, consistency groups and datastore groups Configure array pairs vSphere Replication Explore vSphere Replication architecture Examine vSphere Replication functionality Formulate use cases for vSphere Replication Deploy a vSphere Replication appliance Configure vSphere Replication appliance settings Configure a vSphere Replication appliance connection Deploy a vSphere Replication server Register a vSphere Replication server Replicating Virtual Machines with vSphere Replication Configure vSphere Replication for virtual machines Explain the importance of datastore mappings Describe vSphere Replication recovery point objective scheduling Describe the vSphere Replication disk transfer protocol Building Protection Groups Define protection group functionality Examine the differences between array-based protection groups, protection groups based on vSphere Replication, and storage profile protection groups Create a protection group Discuss protection group settings Remove protection from a virtual machine Create a storage profile protection group Building Recovery Plans Discuss recovery plan concepts List recovery plan steps Discuss network planning Discuss customization options in recovery planning Outline how to implement a recovery plan Investigate recovery plan options Testing and Running a Recovery Plan Discuss use cases for Site Recovery Manager Describe planned migration Identify Site Recovery Manager workflows Discuss the importance of VMware vSphere© VMFS resignaturing Examine Site Recovery Manager integration with various vSphere technologies Outline how to conduct a recovery plan test Perform recovery plan test execution Identify the effects on the storage layer during recovery steps Explain a recovery plan execution in planned migration or disaster recovery mode Understand storage layer changes for plan execution types Identify the recovery steps for each execution type Describe how to reprotect a data center Examine failback steps Monitoring and Troubleshooting Discuss Site Recovery Manager alarms Explore Site Recovery Manager history reports Configuring advanced Site Recovery Manager settings Describe how to modify logging levels Explain how to collect log bundles Identify key log locations

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Platform Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing,storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This 1-day instructor led course introduces Azure professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, Solution Architects and SysOps Administrators familiar with Azure features and setup; and want to gain experience configuring Google Cloud products immediately. With presentations, demos, and hands-on labs, participants get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Identify the purpose of projects on Google Cloud. Understand how Azure's resource hierarchy differs from Google Cloud's Understand the purpose of and use cases for Identity and Access Management. Understand how Azure AD differs from Google Cloud IAM. List the methods of interacting with Google Cloud. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine Understand the basics of networking in Google Cloud. Understand how Azure VPC differs from Google VPC. Understand the similarities and differences between Azure VM and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in Azure. Deploy applications using Google Compute Engine Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Azure Blob compares to Cloud Storage. Compare Google Cloud?s managed database services with Azure SQL. Learn how to choose among the various storage options on Google Cloud. Load data from Cloud Storage into BigQuery Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Azure Kubernetes Service differs from from Google Kubernetes Engine. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Azure App Service. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Google Cloud Deployment Manager differs from Azure Resource Manager. Understand the purpose of integrated monitoring, alerting, and debugging Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from Azure Data Lake. Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from Azure's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from Azure to Google Cloud.

Duration 3 Days 18 CPD hours This course is intended for Team leaders, managers, executives, and other business and IT professionals who lead others as well as Individual contributors ready for transformational self-development as a leader. Overview Recognize vulnerability as the emotion we feel during times of uncertainty, risk, and emotional exposure. Explain why courage requires vulnerability. Establish a link between what I learned and behaviors I want to change. Recognize the critical role that self-awareness plays in daring leadership. Give examples to support how armor - not fear -is the greatest obstacle to daring leadership. Identify the four skill sets that make up courage: rumbling with vulnerability, living into our values, BRAVING trust, and learning to rise. Recognize that courage is a collection of four skill sets that are measurable, observable, and teachable. Recognize that vulnerability is the birthplace of many of the behaviors that define daring leadership, including creativity, accountability, and difficult conversations. Give examples of why daring leadership requires showing up for hard conversations and rumbles, including giving and receiving feedback. This workshop is all about your own leadership self-awareness, identifying your call to courage as a leader and the learning, practice and integration of the four courage skills sets so you can show up authentically in life and leadership. Dare to Lead? is the ultimate playbook for developing brave leaders and courageous cultures. The greatest barrier to daring leadership is not fear; the greatest obstacle is armor ? how we self-protect when we feel uncertainty, risk and emotional exposure. Learn the skills to move from armored leadership to daring leadership. Daring leaders are self-aware, know how to have hard conversations, hold themselves and others accountable, build trust, lead with empathy and connection, take smart risks that lead to innovation, reset quickly after disappointments and setbacks, and give and receive feedback. This interactive curriculum is delivered in five, half-day sessions and is based on the research by Bren‚ Brown. This course comes with a PDF workbook and an Amazon gift card to purchase the Dare to Lead? book in the version of your choice. You also have access to a series of leadership and personal development assessments and exclusive training videos led by Dr. Bren‚ Brown. At the end of the event, a digital badge is awarded to those who complete 24 hours of course content. The Heart of Daring Leadership Permission Slips Container Building Armored Leadership versus Daring Leadership Call to Courage Assembling Our Armor Building Grounded Confidence to Replace our Armor Aplying the 5Cs Self-Awareness & Emotional Literacy Developing Emotional Literacy Getting Curious About Emotions Exploring the Iceberg The Myths of Vulnerability Rumbling with Vulnerability The Six Myths of Vulnerability Exploring Your Arena Shame Resilience Shame 101 Defining Shame The Physiology of Shame Shame Shields How Shame Shows Up in Organizations How Shame Shows up at Work Empathy and Self-Compassion Attributes of Empathy What Does Empathy Look Like? Empathy Misses Comparative Suffering Self-Compassion Talk to Yourself the Way You Talk to Someone You Love Empathy & Self-Compassion Commitment Supplemental Exercise: Kristin Neff?s Self-Compassion Scale Supplemental Exercise: Putting Empathy, Curiosity, and Rumble Tools in Action Living Into Our Values Living Into Our Values Values Clarification Taking Values from Professing Words to Practicing Behaviors Grounded Confidence and Rumbling Skills Grounded Confidence and Rumbling Skills Rumble Starters The 5Cs of Strategic Thinking, Decision Making, and Delegation Using the 5Cs Supplemental Exercise ? Gritty Faith & Gritty Facts Supplemental Exercise ? Horizon Conflict Engaged Feedback Giving Engaged Feedback Recognizing Defensiveness in Feedback Conversations BRAVING Trust BRAVING Trust Square Squad Rumbling with Self-Trust Trust with Others Trust on Teams Rumbling with Living BIG Learning to Rise: The Reckoning Learning to Rise: The Rising Strong Process The Rising Strong Process Getting Emotionally Hooked Offloading Hurt: Barriers to Reckoning with Emotion Strategies for Reckoning with Emotion The Rumble and The Revolution Writing My SFD The Delta The Revolution: When the Process Becomes a Daily Practice Supplemental Exercise ? Reset and Resilience Practices Integration Dare to Lead Integration Plan

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Truth on the Roof is a special project dedicated to conscious storytelling, offering young individuals the opportunity to express themselves and engage in discussions about various social issues through art forms like poetry, music, and spoken word.

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