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N8N The Ultimate Course Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 7.42 GB | Duration: 15h 20m Efficiency Redefined: Crafting Seamless Automations with n8n What you'll learn Understand low-code programming concepts, including variables, conditions, and data types for building efficient workflows. Master N8N's core functionalities to automate tasks using triggers, actions, and various nodes effectively. Learn to create and manage API workflows, integrating external services and handling data transformations seamlessly. Explore advanced features like error handling, debugging, and optimizing workflow performance for real-world applications. Advanced Administration, hosting and database understanding not found elsewhere online or in books Requirements While no experience necessary, as we include several primers that can be skipped by those with experience, this is n8n The Ultimate Course and is for everyone intrested to taking AI and Automations to the next level! Description *** Stop paying - Memberships of $20, $40, $80 and $100+ EACH Month! ***Pay one time here on Udemy!Welcome to "The Ultimate n8n Course," where we embark on a journey through the world of low-code programming and the powerful capabilities of n8n. This course begins by introducing foundational low-code programming concepts, allowing learners to grasp the essential principles that will enable them to make the most of n8n. By understanding these concepts, participants will be well-prepared to explore the n8n interface.As we delve into the n8n interface, learners will discover how to navigate the dashboard effectively. This module highlights the key features of n8n, guiding students in creating their first workflow with ease and confidence.The next phase of the course focuses on the core nodes that constitute n8n. Participants will gain a comprehensive overview of built-in nodes, learning how to work with HTTP request nodes and utilize data transformation nodes to manipulate and manage data efficiently. This knowledge is crucial for developing dynamic workflows.Moving into more advanced topics, we will explore flow nodes, emphasizing flow control and error handling. This module teaches best practices for optimizing workflows, ensuring that students can create robust and efficient automations.Throughout the course, we will also discuss various use cases for n8n. From chat AI processing to agentic AI applications, traditional workflows, and APIs, learners will understand the diverse applications of n8n in real-world scenarios.A significant highlight of this course is the administrative section, where we cover essential topics that are often overlooked in other classes. Students will learn how to install and run n8n locally using Node.js or Docker, as well as in the cloud. We will also introduce easy panel hosting for quick deployments, making the process accessible for everyone.Finally, we'll dive into database management, showing participants how to access the default SQLite database and providing SQL queries for extracting data from PostgreSQL databases. This comprehensive approach ensures that students are well-equipped to leverage n8n for any workflow they envision.Join us in "The Ultimate n8n Course" to unlock the full potential of this dynamic tool and ELEVATE your automation skills to new heights. Overview Section 1: Introduction to Low Code *Programming Concepts Lecture 1 Introduction Lecture 2 Variables Lecture 3 Data Types Lecture 4 Conditions Lecture 5 Collections Lecture 6 Looping Lecture 7 Basic Functions Lecture 8 Advanced Functions Lecture 9 Persistent / Non-Persistent Lecture 10 JSON Section 2: What is N8N and what can you do with it Lecture 11 Introduction Lecture 12 AI Chat, AI Processing & Agentic AI with tooling Lecture 13 Forms Lecture 14 Workflow (Automations) Lecture 15 API (Backend Processing) Section 3: Grounding yourself using n8n (A Day in the Life) Lecture 16 The n8n User Interface Lecture 17 Actions & Triggers Lecture 18 Inputs & Outputs Section 4: Core - NODES Lecture 19 Intro Lecture 20 Code Lecture 21 API Functionality - Webhooks (Inbound) & HTTP Requests (Outbound) Lecture 22 HTTP Lecture 23 Execute a command on the host PC/Server Lecture 24 Execute Another Workflow (Parent > Child concept or modularizing your code) Lecture 25 Execution Data Lecture 26 FTP Lecture 27 n8n (manipulate n8n itself) Lecture 28 Forms Lecture 29 No Operation, do nothing Lecture 30 Wait Section 5: Flow - NODES Lecture 31 Intro Lecture 32 Filter Lecture 33 - IF - Lecture 34 Loop Lecture 35 Merge Lecture 36 Compare Data Sets Lecture 37 Execute Sub Workflow Lecture 38 Stop and Error Lecture 39 Switch Lecture 40 Wait Section 6: Data Transformation - NODES Lecture 41 Intro Lecture 42 Code Lecture 43 Date & Time Lecture 44 Edit Fields (Set), aka Variables. Lecture 45 Filter Lecture 46 Limit Lecture 47 Remove Duplicates Lecture 48 Split Out Lecture 49 Aggregate Lecture 50 Merge Lecture 51 Sumamrize Lecture 52 Compression Lecture 53 Convert to File Lecture 54 Crypto Lecture 55 Edit Image Lecture 56 Extract from File Lecture 57 HTML (See Class Assets) Lecture 58 Markdown Lecture 59 XML Lecture 60 Rename Keys Lecture 61 Sort Section 7: n8n and all things AI+ Lecture 62 Kinds of AI Lecture 63 AI Chatbots Lecture 64 Retrieval Augmented Generation (RAG) Lecture 65 Upserting - to - Retrieval Augmented Generation (RAG) Lecture 66 Publishing a Chatbot and customizing it Lecture 67 AI in API's & Workflow Operations Lecture 68 Model Context Protocol (MCP) - SERVER & CLIENT - Best Toolbox Ever!!! Lecture 69 AI Models Lecture 70 Understanding Model Quantization, Parameters, and Context Lengths Lecture 71 Governance with LITELLM & Langfuse Lecture 72 AI Assisted Coding (VIBE Coding) front end / n8n back end *optional bonus video* Section 8: Administration & Installation Lecture 73 Installation using NODE Lecture 74 Installation using Docker Lecture 75 Installation using EasyPanel Lecture 76 Free Hosting at Home (You must leave your PC on 24x7) Lecture 77 Database and Reporting Lecture 78 Environmental Variables Lecture 79 n8n System Settings Lecture 80 Licensing Section 9: Configuring the Harder Cloud Credentials Lecture 81 API KEY - Simplest and most often used, use case Lecture 82 Google Cloud Console Lecture 83 Azure EntraID / App Registrations Section 10: Resources, Examples and Templates Lecture 84 My Sainsbury Templates Lecture 85 Consulting Lead Gen Lecture 86 SQL Server Test Database (Backup) Lecture 87 My Linked in Posting Template Beginners looking to dive into low-code development and Agentic AI automation.,Developers wanting to enhance their skills in Agentic AI workflow automation with N8N.,Business Analysts aiming to streamline business processes without extensive coding knowledge powered by AI.,Entrepreneurs seeking efficient ways to automate tasks and improve productivity with AI and Agentic AI.,Tech Professionals wanting to implement agentic AI solutions for enhanced task automation.,AI Enthusiasts eager to explore the integration of AI and automation in workflows. 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Navigating Burnout Through Self-Compassion Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 449.64 MB | Duration: 1h 4m Understanding Burnout and Building Resilience Through Self-Compassion and Emotional Regulation What you'll learn Define burnout and identify its key symptoms, including emotional exhaustion, depersonalisation, and reduced motivation. Distinguish burnout from general stress and understand its progression through the five stages, from the honeymoon phase to habitual burnout. Identify personal and occupational risk factors that contribute to burnout, including workload, workplace dynamics, and external stressors. Recognise the psychological, physical, and professional consequences of chronic burnout, such as decreased job satisfaction, emotional blunting, and relational Understand the 3-System Model of Emotion Regulation (threat, drive, and soothing systems) and how imbalances contribute to burnout. Explore the concept of self-compassion, including its three components-mindfulness, self-kindness, and common humanity-and its distinction from self-esteem. Challenge common misconceptions about self-compassion, such as the belief that it leads to weakness or indulgence. Describe the benefits of self-compassion for emotional resilience, mental well-being, and overall stress reduction. Practise evidence-based techniques to cultivate a self-compassionate mindset, such as journaling, gratitude, and setting healthy boundaries. Develop a personalised plan to integrate self-compassion into daily life, fostering sustained mental health and emotional balance. Requirements No requirments needed Description Burnout is more than just feeling tired or overworked-it is a state of deep emotional, physical, and mental exhaustion that can significantly impact your health, relationships, and overall life satisfaction. Often driven by prolonged stress, burnout can leave you feeling disconnected, demotivated, and overwhelmed. This course offers a structured, evidence-based approach to understanding burnout and using self-compassion as a powerful tool for recovery, resilience, and long-term well-being.You will begin by exploring what burnout truly is-how it differs from general stress, how it presents in the body and mind, and why it often goes unrecognised until it becomes chronic. The course outlines the most common causes and risk factors, including workplace demands, lack of control, misalignment with personal values, and external pressures. You will also learn about the five distinct stages of burnout and how to identify them in yourself or others.A central theme of the course is self-compassion-a concept often misunderstood but proven to reduce stress, improve emotional balance, and foster psychological resilience. You'll be introduced to the three-system model of emotion regulation (threat, drive, and soothing systems) and gain insight into how internal emotional patterns contribute to burnout.Through a combination of theory, reflective exercises, and guided practices such as the Self-Compassion Break, this course equips you with practical tools to integrate self-care and emotional awareness into daily life. By the end, you'll be empowered with the knowledge and skills to recognise early signs of burnout, respond with kindness rather than criticism, and take proactive steps toward sustained mental and emotional well-being. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Definition of Burnout Lecture 3 Symptoms of Burnout Lecture 4 Causes and risk factors Lecture 5 Physical, psychological and occupational impact Section 2: How do we burn out? Lecture 6 Understanding the progression of Burnout Lecture 7 Applying the 3-system model of emotion regulation to understanding burnout Section 3: The role of Self-compassion in managing burnout Lecture 8 Definition and components of Self-compassion Lecture 9 Dispelling common myths about Self-compassion Lecture 10 How Self-compassion helps in navigating Burnout Section 4: Practical strategies for cultivating a Self-compassionate mindset Lecture 11 Integrating Self-compassion into daily life Lecture 12 Guided meditation practice Professionals,Anyone who is interested how to navigate burnout,Medical Field,Students,Caregivers DDownload https://ddownload.com/ti18eqpd4xra/yxusj.Navigating.Burnout.Through.SelfCompassion.rar RapidGator https://rapidgator.net/file/59f679181e4fd9b49f4f085c0dcbf66e/yxusj.Navigating.Burnout.Through.SelfCompassion.rar NitroFlare https://nitroflare.com/view/B29638F78780D06/yxusj.Navigating.Burnout.Through.SelfCompassion.rar

Microsoft Purview Information Security Administrator Course Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.32 GB | Duration: 8h 6m Learn how to expertly administer Microsoft Purview with hands on experience! What you'll learn Learn the concepts and perform hands on activities needed to master Microsoft Purview Gain a tremendous amount of knowledge involving Microsoft Purview Learn using hands on simulations on how Microsoft Purview is administered! Learn how to set up your own test lab for practicing the concepts! Requirements Willingness to put in the time and practice the steps shown in the course Description We really hope you'll agree, this training is way more than the average course on Udemy! Have access to the following:Training from an instructor of over 20 years who has trained thousands of people and also a Microsoft Certified TrainerLecture that explains the concepts in an easy to learn method for someone that is just starting out with this materialInstructor led hands on and simulations to practice that can be followed even if you have little to no experienceTOPICS COVERED INCLUDING HANDS ON LECTURE AND PRACTICE TUTORIALS:IntroductionWelcome to the course!Understanding the Microsoft 365 and Azure EnvironmentA Solid Foundation of Active Directory DomainsA Solid Foundation of RAS, DMZ, and VirtualizationA Solid Foundation of the Microsoft Cloud ServicesDONT SKIP: Before beginning your account setupCreating a trial Microsoft 365/Azure AccountIMPORTANT Using Assignments in the courseQuestions for John ChristopherCertificate of CompletionUsing Data Classification and Sensitivity Label in Microsoft PurviewIntroducing the new Microsoft Purview portalUnderstanding requirements for sensitive informationConcepts of built-in or custom sensitive information requirementsCreating custom sensitive info typesDocument FingerprintingWorking with exact data match (EDM) classifiersUnderstanding trainable classifiersWorking with trainable classifiersUsing data explorer & content explorer for monitoring data classificationSensitive info types with optical character recognition (OCR)Understanding sensitivity labelsAdministering permissions for sensitivity labelsCreating sensitivity labelsSensitivity label protection settings and content markingPublishing sensitivity labels in Microsoft PurviewUsing auto-labeling policies for sensitivity labelsControlling sensitivity label to containersHow users can apply sensitivity labels manually using Microsoft WordConcepts of Microsoft Defender for Cloud AppsHow Microsoft Defender for Cloud Apps can apply sensitivity labelsUsing Microsoft Purview for information protection of clients and dataConcepts of the Microsoft Purview Information Protection ClientSetting up the Microsoft Purview Information Protection ClientUsing the Microsoft Purview Information Protection client to manage filesUnderstanding MS Purview Information Protection scanner bulk classificationsDeleting the Azure VM that is no longer neededUnderstanding the Microsoft 365 email Encryption solutionsMicrosoft Purview Message EncryptionMicrosoft Purview Advanced Message EncryptionUsing Data Loss Prevention with Microsoft PurviewUnderstanding data loss prevention policiesData loss prevention roles and permissionsCreating data loss prevention policiesUsing Adaptive Protection with data loss preventionData loss prevention policy and rule precedenceUsing Defender for Cloud apps to deploy DLP file policiesConcepts of Endpoint DLP device requirementsSettings used to manage Endpoint DLPManaging DLP policies using the advanced rulesWorking with just-in-time (JIT) protectionHow to monitor endpoint activitiesUsing and maintaining retention in Microsoft PurviewUnderstanding information retention and dispositionRetention Policies vs Retention Labels vs Retention Label PoliciesUsing adaptive scopesCreating retention labelsPublishing a retention label using a label policyUsing auto-apply labels for retentionUnderstanding policy precedence in regards to conflictsCreating retention policiesConcepts for recovering retained content in Microsoft 365Using Insider Risk Management in Microsoft PurviewUnderstanding Insider Risk Management in Microsoft 365Concepts of Insider Risk Management roles and permissionsUsing Insider Risk Management connectorsManaging Insider Risk Management settingsManaging the settings for policy indicatorsUnderstanding the concepts of policy templatesCreating Insider Risk Management policiesWorking with forensic evidence settingsManaging insider risk levels for Adaptive ProtectionInsider risk alerts and casesUsing notice templates within Insider Risk ManagementUsing alert monitoring and protecting data used by AI servicesUnderstanding the license concepts for Microsoft Purview Audit (Premium)\Looking into activities by using Microsoft Purview AuditWorking with audit retention policiesUsing activity explorer to analyze Microsoft Purview activitiesData loss prevention alerts in Microsoft PurviewViewing insider risk activitiesViewing Purview alerts in Microsoft Defender XDRWorking with file policy alerts using Defender for Cloud AppsPerforming content searchesUnderstanding controls for the AI services in Microsoft PurviewConcepts of Microsoft 365 workload controlsSetting up a Windows 11 VM for hands onSetting up the pre-requisites involving DSPM for AIAI policies with DSPMDSPM for AI activity monitoringDeleting the Windows 11 VM from the lab Overview Section 1: Introduction Lecture 1 Understanding the Microsoft 365 and Azure Environment Lecture 2 A Solid Foundation of Active Directory Domains Lecture 3 A Solid Foundation of RAS, DMZ, and Virtualization Lecture 4 A Solid Foundation of the Microsoft Cloud Services Lecture 5 DONT SKIP: Before beginning your account setup Lecture 6 Creating a trial Microsoft 365/Azure Account Lecture 7 DON'T SKIP: Using Assignments in the course Lecture 8 Questions for John Christopher Lecture 9 Certificate of Completion Section 2: Using Data Classification and Sensitivity Label in Microsoft Purview Lecture 10 Introducing the new Microsoft Purview portal Lecture 11 Understanding requirements for sensitive information Lecture 12 Concepts of built-in or custom sensitive information requirements Lecture 13 Creating custom sensitive info types Lecture 14 Document Fingerprinting Lecture 15 Working with exact data match (EDM) classifiers Lecture 16 Understanding trainable classifiers Lecture 17 Working with trainable classifiers Lecture 18 Using data explorer & content explorer for monitoring data classification Lecture 19 Sensitive info types with optical character recognition (OCR) Lecture 20 Understanding sensitivity labels Lecture 21 Administering permissions for sensitivity labels Lecture 22 Creating sensitivity labels Lecture 23 Sensitivity label protection settings and content marking Lecture 24 Publishing sensitivity labels in Microsoft Purview Lecture 25 Using auto-labeling policies for sensitivity labels Lecture 26 Controlling sensitivity label to containers Lecture 27 How users can apply sensitivity labels manually using Microsoft Word Lecture 28 Concepts of Microsoft Defender for Cloud Apps Lecture 29 How Microsoft Defender for Cloud Apps can apply sensitivity labels Lecture 30 DONT SKIP: Redoing simulations in the course Section 3: Using Microsoft Purview for information protection of clients and data Lecture 31 Concepts of the Microsoft Purview Information Protection Client Lecture 32 Setting up the Microsoft Purview Information Protection client Lecture 33 Using the Microsoft Purview Information Protection client to manage files Lecture 34 Understanding MS Purview Information Protection scanner bulk classifications Lecture 35 Deleting the Azure VM that is no longer needed Lecture 36 Understanding the Microsoft 365 email Encryption solutions Lecture 37 Microsoft Purview Message Encryption Lecture 38 Microsoft Purview Advanced Message Encryption Section 4: Using Data Loss Prevention (DLP) with Microsoft Purview Lecture 39 Understanding data loss prevention policies Lecture 40 Data loss prevention roles and permissions Lecture 41 Creating data loss prevention policies Lecture 42 Using Adaptive Protection with data loss prevention Lecture 43 Data loss prevention policy and rule precedence Lecture 44 Using Defender for Cloud apps to deploy DLP file policies Lecture 45 Concepts of Endpoint DLP device requirements Lecture 46 Settings used to manage Endpoint DLP Lecture 47 Managing DLP policies using the advanced rules Lecture 48 Working with just-in-time (JIT) protection Lecture 49 How to monitor endpoint activities Section 5: Using and maintaining retention in Microsoft Purview Lecture 50 Understanding information retention and disposition Lecture 51 Retention Policies vs Retention Labels vs Retention Label Policies Lecture 52 Using adaptive scopes Lecture 53 Creating retention labels Lecture 54 Publishing a retention label using a label policy Lecture 55 Using auto-apply labels for retention Lecture 56 Understanding policy precedence in regards to conflicts Lecture 57 Creating retention policies Lecture 58 Concepts for recovering retained content in Microsoft 365 Section 6: Using Insider Risk Management in Microsoft Purview Lecture 59 Understanding Insider Risk Management in Microsoft 365 Lecture 60 Concepts of Insider Risk Management roles and permissions Lecture 61 Using Insider Risk Management connectors Lecture 62 Managing Insider Risk Management settings Lecture 63 Managing the settings for policy indicators Lecture 64 Understanding the concepts of policy templates Lecture 65 Creating Insider Risk Management policies Lecture 66 Working with forensic evidence settings Lecture 67 Managing insider risk levels for Adaptive Protection Lecture 68 Insider risk alerts and cases Lecture 69 Using notice templates within Insider Risk Management Section 7: Using alert monitoring and protecting data used by AI services Lecture 70 Understanding the license concepts for Microsoft Purview Audit (Premium) Lecture 71 Looking into activities by using Microsoft Purview Audit Lecture 72 Working with audit retention policies Lecture 73 Using activity explorer to analyze Microsoft Purview activities Lecture 74 Data loss prevention alerts in Microsoft Purview Lecture 75 Viewing insider risk activities Lecture 76 Viewing Purview alerts in Microsoft Defender XDR Lecture 77 Working with file policy alerts using Defender for Cloud Apps Lecture 78 Performing content searches Lecture 79 Understanding controls for the AI services in Microsoft Purview Lecture 80 Concepts of Microsoft 365 workload controls Lecture 81 Setting up a Windows 11 VM for hands on Lecture 82 Setting up the pre-requisites involving DSPM for AI Lecture 83 AI policies with DSPM Lecture 84 DSPM for AI activity monitoring Lecture 85 Deleting the Windows 11 VM from the lab Lecture 86 Getting your Udemy certificate for this course IT people interested in learning a tremendous amount about Microsoft Purview DDownload https://ddownload.com/selbtt3scnv3/yxusj.Microsoft.Purview.Information.Security.Administrator.Course.part1.rar https://ddownload.com/51npcacn56sf/yxusj.Microsoft.Purview.Information.Security.Administrator.Course.part2.rar https://ddownload.com/kd5dckno6dfd/yxusj.Microsoft.Purview.Information.Security.Administrator.Course.part3.rar https://ddownload.com/2pptm7dpsot7/yxusj.Microsoft.Purview.Information.Security.Administrator.Course.part4.rar https://ddownload.com/4kx00aunwg27/yxusj.Microsoft.Purview.Information.Security.Administrator.Course.part5.rar RapidGator 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Microsoft Power Bi - Master Data Visualizations Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.45 GB | Duration: 2h 15m Data Visualization What you'll learn Data Visualization Data Analysis & Insights Findings Data Manipulation with Case Study Story Telling for Businesses and Academics Requirements No Programming Knowledge Required. You will get what you need Description Power BI is one of the most powerful tools for transforming raw data into meaningful insights through rich, interactive reports and dashboards. In this course, you will learn how to leverage Power BI's vast array of features to create stunning visualizations, analyze data, and share actionable insights with your team or stakeholders. From the basics of data import and transformation to advanced features like DAX, Power Query, and interactive report building, this course will give you the skills to become proficient in Power BI. Whether you're a beginner or an experienced user, this course provides practical examples and real-world use cases to help you master data analysis.What is Power BI and its role in data analysis?Overview of Power BI components: Power BI Desktop, Power BI Service, and Power BI MobileKey differences between Power BI and other BI tools (e.g., Tableau, Excel)Understanding the Power BI workspaceNavigating the Power BI interface and understanding its features1. Overview2. All Visuals3. Visuals Dashboard4. Dashboard5. Dax Columns6. DAX Measure7. Power Query8. Complex Query9. Dashboard10. Tricks11. Python over Power BI12. 3D Models in Power BI13. Book-Mark14. Freezing visual Overview Section 1: Introduction Lecture 1 Power BI Introduction Lecture 2 Overview Lecture 3 All Visuals Lecture 4 Distinct Lecture 5 Data Analytical Expression (DAX)- Columns Lecture 6 DAX Measures Lecture 7 Power Query Lecture 8 Calendar Function Lecture 9 BookMark Lecture 10 Freezing Visuals and Parameters Data Visualization beginners who are curious about data insights RapidGator https://rapidgator.net/file/e7dd537b07b5294912b0d749bbe40993/microsoft.power.bi..master.data.visualizations.part1.rar https://rapidgator.net/file/3077f7351a54999b9a0b0df9286ab9c3/microsoft.power.bi..master.data.visualizations.part2.rar NitroFlare https://nitroflare.com/view/D7C24BBE3AF1713/microsoft.power.bi..master.data.visualizations.part1.rar https://nitroflare.com/view/3690AB0236385CA/microsoft.power.bi..master.data.visualizations.part2.rar DDownload https://ddownload.com/x8p8dvejnic2/microsoft.power.bi..master.data.visualizations.part1.rar https://ddownload.com/s97xt81rodcc/microsoft.power.bi..master.data.visualizations.part2.rar

Mental Health And Wellbeing: Strategies For A Healthier Mind Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 172.36 MB | Duration: 1h 7m A practical guide to understanding, managing, and improving mental health and emotional wellbeing What you'll learn Understand the foundations of mental health and emotional wellbeing Identify common mental health challenges such as stress, anxiety, and depression Apply practical strategies to manage negative thoughts and build emotional resilience Develop healthy coping mechanisms to deal with life's stressors Improve self-awareness, self-esteem, and emotional intelligence Establish daily habits that support long-term mental wellness Recognize when and how to seek professional mental health support Requirements NO requirements or prerequisites Description Mental health is no longer a topic we can afford to ignore. In a world filled with constant stressors, emotional pressure, and overwhelming demands, taking care of your mental and emotional wellbeing has become a vital part of living a healthy, balanced life. This course is designed to give you the knowledge, tools, and confidence to understand your mind, strengthen your emotional resilience, and take practical steps toward long-lasting mental wellness.Throughout this course, you'll explore the core foundations of mental health-what it really means, why it matters, and how it affects every area of your life. You'll learn how to recognize common mental health challenges such as stress, anxiety, depression, and burnout, and discover actionable strategies to manage them effectively. Whether you're looking to support yourself or help others in your personal or professional life, this course offers a compassionate, comprehensive, and empowering approach.One of the most powerful aspects of this course is its emphasis on practical application. You won't just learn theory-you'll be guided through self-assessments, reflective exercises, and real-world techniques that you can apply immediately. You'll develop daily habits that promote emotional balance, build mental strength, and enhance your self-awareness. From mindfulness and cognitive reframing to goal setting and self-care routines, this course covers a full spectrum of proven strategies for emotional wellness.This course is ideal for anyone who wants to take proactive control of their mental wellbeing. It's equally valuable for individuals experiencing stress or low mood, as well as for professionals such as coaches, educators, managers, or caregivers who want to better support the mental health of others. No prior experience or background in psychology is required-this course is beginner-friendly, yet rich in practical insights.By the end of the program, you'll walk away with a deep understanding of mental health, renewed clarity about your emotional patterns, and a personalized wellbeing plan you can follow for life. More importantly, you'll feel empowered-more resilient, self-aware, and capable of facing life's challenges with calm and confidence.Investing in your mental health is one of the most powerful decisions you can make-not just for yourself, but for the people around you. Enroll today and begin your journey toward greater mental clarity, emotional balance, and lasting wellbeing. Overview Section 1: Introduction to Mental Health Lecture 1 Introduction to Mental Health Lecture 2 The Role of a Mental Health Lecture 3 Understanding the Mind-Body Connection Lecture 4 Different Perspectives on Mental Lecture 5 The Biopsychosocial Model Explained Section 2: Common Mental Health Disorders Lecture 6 Common Mental Health Disorders Lecture 7 Depression_ Causes, Symptoms Lecture 8 Anxiety and Stress-Related Disorders Lecture 9 Bipolar Disorder_ Recognition Anyone looking to improve their mental health and emotional wellbeing,Individuals experiencing stress, burnout, anxiety, or low mood,HR professionals, educators, and team leaders who support others in challenging environments,Students and professionals who want to build mental resilience and emotional intelligence,People interested in self-development, mindfulness, and holistic wellbeing,Beginners with no prior knowledge of mental health looking for a comprehensive starting point RapidGator https://rapidgator.net/file/d3c88c0d5beb49b8f19704ea6a4e4055/mental.health.and.wellbeing.strategies.for.a.healthier.mind.rar NitroFlare https://nitroflare.com/view/773EE1E10018231/mental.health.and.wellbeing.strategies.for.a.healthier.mind.rar DDownload https://ddownload.com/9dt5k3b574tl/mental.health.and.wellbeing.strategies.for.a.healthier.mind.rar

Multiple Regression in Minitab - Tabtrainer® Backward Guide Last updated 5/2025 Duration: 53m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 337 MB Genre: eLearning | Language: English Model industrial data with Minitab using backward elimination - reduce predictors, detect multicollinearity What you'll learn - Understand the basics of multiple regression analysis and apply it to real-world industrial data involving both continuous and categorical predictors. - Conduct a full regression workflow including data import, exploration, matrix plots, and hypothesis testing to assess initial trends and relationships. - Interpret correlation coefficients and determine whether linear relationships between variables are statistically significant using p-values - Evaluate the effect of individual predictors on the response variable using p-values and model coe - Apply and interpret the Variance Inflation Factor (VIF) to detect and assess multicollinearity between predictor variables. - Perform step-by-step backward elimination, removing non-significant predictors iteratively to simplify the model while preserving statistical integrity. - Use adjusted R-squared and predicted R-squared to evaluate and compare the goodness-of-fit of different regression models, ensuring model validity and predictiv - Assess model assumptions through residual analysis, including normality, homoscedasticity, and independence, using "Four-in-One" diagnostic plots. - Execute automated backward elimination and understand its benefits compared to manual iterative elimination, especially in high-dimensional models. - Apply best subsets regression to identify the most influential predictors under practical constraints and interpret advanced model quality parameters such as Ma Requirements - No Specific Prior Knowledge Needed: all topics are explained in a practical step-by-step manner. Description Welcome to this data-driven course from theTabtrainer® Certified Series- your trusted platform for industrial analytics and applied regression modeling. In this course, you'll learn to build, refine, and interpretmultiple linear regression modelsinMinitab, using a real production case from theSpeedboard Company. You'll apply bothmanual and automated backward eliminationto identify the most relevant predictors, reduce model complexity, and maintain statistical integrity. From correlation analysis andVIF-based multicollinearity checksto advanced model diagnostics andbest subsets regression, this training equips you to make confident, evidence-based decisions in industrial quality, R&D, and process optimization. Led byProf. Dr. Murat Mola, TÜV-certified expert, industrial consultant, andProfessor of the Year 2023 in Germany, this course bridges academic depth with practical relevance under the trusted brandTabtrainer®. The course Multiple Regression with Backward Elimination teaches participants how to: Analyze industrial datawith multiple continuous and categorical predictors. Apply backward elimination, interpret p-values, VIFs, and residuals, and use best subsets regression for model simplification. Emphasis is placed on practical model optimization and real-world decision-making: Understand the basics of multiple regression analysisand apply it to real-world industrial data involving both continuous and categorical predictors. Conduct a full regression workflowincluding data import, exploration, matrix plots, and hypothesis testing to assess initial trends and relationships. Interpret correlation coefficientsand determine whether linear relationships between variables are statistically significant using Pearson correlation and p-values. Evaluate the effect of individual predictors(e.g., deck width, wheel hardness, deck flex) on the response variable (maximum speed) using p-values and model coefficients. Apply and interpret the Variance Inflation Factor (VIF)to detect and assess multicollinearity between predictor variables. Perform step-by-step backward elimination, removing non-significant predictors iteratively to simplify the model while preserving statistical integrity. Use adjusted R-squared and predicted R-squaredto evaluate and compare the goodness-of-fit of different regression models, ensuring model validity and predictive quality. Assess model assumptions through residual analysis, including normality, homoscedasticity, and independence, using "Four-in-One" diagnostic plots. Execute automated backward eliminationand understand its benefits compared to manual iterative elimination, especially in high-dimensional models. Apply best subsets regressionto identify the most influential predictors under practical constraints and interpret advanced model quality parameters such as Mallows Cp, PRESS, AICc, and BIC. Who this course is for: - Six Sigma Practitioners: Professionals looking to enhance their expertise in statistical tools for process optimization and decision-making. - Quality Assurance Professionals: Those responsible for monitoring production processes and ensuring product quality will gain practical tools for defect analysis. - Production Managers: Managers overseeing manufacturing operations will benefit from learning how to identify and address quality issues effectively. - Engineers and Analysts: Individuals in manufacturing or technical roles seeking to apply statistical methods to real-world challenges in production. - Business Decision-Makers: Executives and leaders aiming to balance quality, cost, and efficiency in production through data-driven insights and strategies. 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Minitab® Tabtrainer Series: Full Factorial D.O.E. Mastery Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 517.92 MB | Duration: 1h 40m Design of Experiments (DOE) with Center Points, Blocking, and Optimization in Minitab® What you'll learn Use Minitab to build full factorial designs, set center points, and define blocks for testing multiple factors like roughness, seam width, and thickness. Perform power analysis in Minitab to calculate the number of replicates needed to detect a specific mean shift in the response variable with 80% certainty. Insert center points in Minitab to detect nonlinear behavior between factors and validate the linear model assumptions using p-values from t-tests. Add blocks in Minitab to separate variance caused by external factors like different test pilots, ensuring clean analysis of primary factors. Run D.O.E. analysis via "Analyze Factorial Design" to check which factors significantly impact the response using p-values and coded coefficients. Visualize effects with Minitab's factorial plots and interval plots to detect main effects and interactions influencing the cd value. Improve model quality by removing non-significant terms using manual or automated backward elimination while preserving model hierarchy. Evaluate model quality using R-squared, adjusted R-squared, and predicted R-squared in Minitab to assess precision and prediction power. Check the model residuals with the 4-in-1 residual plot to ensure normality, homoscedasticity, and absence of time-based trends. Use Minitab's response optimizer to dynamically adjust factor settings and visually identify optimal parameter combinations for cd reduction. Use contour plots to visualize factor interactions, define robust process windows, and make reliable decisions even under process variation Analyze cube plots to compare mean responses at all design points, identify optimal settings, and recognize non-linear effects across the factor space. Rotate and edit surface plots to explore predicted responses in 3D space, validate model accuracy, and present results clearly in technical discussions. Requirements No Specific Prior Knowledge Needed: all topics are explained in a practical step-by-step manner. Description Welcome to the Tabtrainer® Certified Series - your expert platform for advanced statistical quality improvement using Minitab®.In this course, you'll master full factorial Design of Experiments (DOE) with a special focus on integrating center points and blocking - powerful techniques that bring real-world robustness to your experimental designs.You'll learn how to structure experiments in Minitab®, detect curvature with center points, control for external noise using blocking variables, and use power analysis to ensure your design's sensitivity. Through real industrial cases, you'll perform ANOVA, regression, and optimization using Minitab's Response Optimizer to derive statistically sound, actionable recommendations.Taught by Prof. Dr. Murat Mola, TÜV-certified Six Sigma expert and Professor of the Year 2023 in Germany, this course equips engineers, technicians, and Six Sigma professionals with the advanced skills needed to make data-driven decisions and optimize complex manufacturing processes.Course Description:This comprehensive training course is your step-by-step guide to mastering full factorial Design of Experiments (D.O.E.) using Minitab®, the industry-leading software for statistical analysis and quality improvement. Designed for engineers, quality managers, Six Sigma practitioners, and analysts, this course combines robust statistical theory with practical application inside Minitab's user-friendly interface.You will begin by learning how to create full factorial experimental designs in Minitab, including the integration of center points and blocking structures to account for real-world factors like operator variability or process instability. With Minitab's intuitive dialogs, you'll learn to calculate statistical power, determine the required number of replicates, and ensure that your design can detect meaningful effects with high sensitivity.As the course progresses, you will perform detailed ANOVA and regression analysis using Minitab's analysis tools. You'll interpret coded coefficients, p-values, F-values, and t-statistics, and generate factorial plots and Pareto charts to visualize the significance of main effects and interactions. You'll also use stepwise regression and hierarchical backward elimination to optimize your model without violating the model hierarchy.Minitab's Four-in-One residual plots, normality tests, and variance inflation factors (VIF) will help you validate your model and confirm assumptions like normality and homoscedasticity.In the final section, you'll use the Minitab Response Optimizer with dynamic sliders to explore the optimal settings for your process parameters. You will learn how to visualize individual and composite desirability, interpret confidence and prediction intervals, and make data-driven recommendations with up to 95% statistical certainty.To support clear communication and effective stakeholder alignment, you'll also master three powerful visualization tools: Contour plots help you define robust process windows at a glance, identifying ideal factor combinations even under variation. Cube plots allow you to detect nonlinear effects and compare average responses across all design points in your experimental space. Finally, surface plots enable you to explore predictive model behavior in a dynamic 3D view-ideal for technical discussions and presentations where clarity and precision matter.Whether you are preparing for a Six Sigma project or aiming to bring your process optimization to a new level, this course gives you practical Minitab® skills and a deep understanding of factorial design principles-applied to a real-world engineering case.Keywords (SEO): Minitab DOE course, full factorial design with Minitab, response optimization, Minitab training, Six Sigma statistics, design of experiments tutorial, ANOVA in Minitab, regression analysis, Minitab Response Optimizer, process optimization tools. Overview Section 1: Tabtrainer Series: Full Factorial D.O.E. with Centerpoints and Blocks - Part 1 Lecture 1 Explore the curriculum Lecture 2 Business Case and Process Understanding Lecture 3 Understanding Type I & II Errors in Full Factorial D.O.E. Lecture 4 Power Analysis in Full Factorial Design Using Minitab Lecture 5 Optimizing Experimental Sensitivity in Full Factorial Design with Minitab Lecture 6 Enhancing Experimental Rigor in Full Factorial Designs Section 2: Tabtrainer Series: Full Factorial D.O.E. with Centerpoints and Blocks - Part 2 Lecture 7 Implementing a Full Factorial Design with Center Points and Blocks Lecture 8 Finalizing Full Factorial Design Lecture 9 Visualizing Factorial Results Section 3: Tabtrainer Series: Full Factorial D.O.E. with Centerpoints and Blocks - Part 3 Lecture 10 Analyzing Factorial Effects Lecture 11 Visualizing Effects & Interactions Lecture 12 R² Metrics and Variance Analysis in Minitab® Lecture 13 Interpreting ANOVA and Regression Equations in Full Factorial D.O.E. Lecture 14 Hierarchical Model Refinement in Full Factorial D.O.E. Lecture 15 Automated Model Optimization & Residual Validation Section 4: Tabtrainer Series: Full Factorial D.O.E. with Centerpoints and Blocks - Part 4 Lecture 16 Response Optimization in Minitab® Lecture 17 Interactive Optimization in Minitab®: Fine-Tuning Parameters Lecture 18 Contour, Cube & Surface Plots for DOE Optimization Lecture 19 Summary of the Most Important Findings Data Analysts, Six Sigma Belts, Minitab Process Optimizers, Minitab Users,Quality Assurance Professionals: Those responsible for monitoring production processes and ensuring product quality will gain practical tools for defect analysis.,Production Managers: Managers overseeing manufacturing operations will benefit from learning how to identify and address quality issues effectively.,Six Sigma Practitioners: Professionals looking to enhance their expertise in statistical tools for process optimization and decision-making.,Engineers and Analysts: Individuals in manufacturing or technical roles seeking to apply statistical methods to real-world challenges in production.,Business Decision-Makers: Executives and leaders aiming to balance quality, cost, and efficiency in production through data-driven insights and strategies. 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