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Course Curriculum Applications on Matrices in MATLAB Solving One Non Linear Equation in MATLAB Using Fzero Function 00:15:00 Example 1 on Solving Multiple Non Linear Equations in MATLAB Using Fsolve 00:14:00 Example 2 on Solving Multiple Non Linear Equations in Matlab Using Fsolve 00:12:00 Application Multi Level Inverter Part 1 00:24:00 Application Multi Level Inverter Part 2 00:04:00 Power Electronics Simulations Using Simulink in MATLAB Introduction to MATLAB Simulations Using Simulink 00:03:00 Half Wave Uncontrolled Rectifier Principle of Operation 00:21:00 Half Wave Controlled Rectifier Principle of Operation 00:04:00 Simulation of Half Wave Controlled Rectifier In MATLAB 00:25:00 Simulation of Bridge Controlled Rectifier in MATLAB 00:16:00 AC Chopper with R Load Principle of Operation 00:14:00 Simulation of AC Chopper with R and RL Loads in MATLAB 00:10:00 Buck Regulator Principle of Operation Part 1 00:16:00 Buck Regulator Principle of Operation Part 2 00:16:00 Simulation of Buck Regulator in MATLAB 00:14:00 Boost Regulator Principle of Operation 00:23:00 Simulation of Boost Regulator in MATLAB 00:12:00 Buck-Boost Regulator Principle of Operation 00:17:00 Simulation of Buck-Boost Regulator in MATLAB 00:09:00 Single Phase Half Bridge Inverter Principle of Operation 00:15:00 Simulation of Single Phase Half Bridge Inverter in MATLAB 00:17:00 Single Phase Bridge Principle of Operation 00:05:00 Simulation of Single Phase Bridge Inverter in MATLAB 00:10:00 Three Phase Inverter Obtaining The Line Voltage 00:14:00 Three Phase Inverter Obtaining The Phase Voltage 00:17:00 Simulation of Three Phase Inverter in MATLAB 00:17:00 Simulation of Charging and Discharging Capacitor Using MATLAB 00:10:00 Solar Energy Simulation Using Simulink in MATLAB and ETAP Simulation of PV Cell In MATLAB and Obtaining V-I Characteristics 00:28:00 Get a Complete Grid-Connected PV System For Free 00:25:00 Simulation of PV System in ETAP 00:24:00 DC Motor Simulation Using Simulink in MATLAB Separately Excited DC Motor Principle of Operation 00:20:00 DC Motor Modelling without Load Using Simulink in MATLAB 00:24:00 DC Motor Modelling with Load Using Simulink in MALTAB 00:23:00 DC Motor Block Simulation Using Power Library in MATLAB 00:16:00 Induction Motor Simulation Using Simulink in MATLAB Construction and Theory of Operation of Induction Machines 00:27:00 Equivalent Circuit and Power Flow in Induction Motor 00:23:00 Torque-Speed Characteristics of Induction Motor 00:19:00 Simulation of Induction Motor or Asynchronous Motor Using Simulink 00:33:00 Synchronous Generator Simulation in Simulink of MATLAB Construction and Principle of Operation of Synchronous Generator 00:33:00 Equivalent Circuit and Phasor Diagram of Non Salient Synchronous Machine 00:29:00 Equivalent Circuit and Phasor Diagram of Salient Synchronous Machine 00:38:00 Simulation of Synchronous Machine Connected to Small Power System 00:37:00 Power System Simulations Importing Data from PSCAD Program for Fault Location Detection to MATLAB Program 00:37:00 PID Controller in MATLAB How to Implement PID Controller in Simulink of MATLAB 00:14:00 Tuning a PID Controller In MATLAB Simulink 00:17:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00
Students who complete the PV351 workshop will be able to: Determine use and analyze results from various test tools used during commissioning, performance evaluation, operations and maintenance, and troubleshooting. Define the theory, procedures, and processes behind insulation resistance testing, IV curve tracing, infrared cameras and thermal imaging, performance evaluation, and troubleshooting Demonstrate proper set-up, use, and function of PV test tools including: IV curve tracers, insulation resistance testers, and thermal cameras Evaluate the performance of working systems using correct and complete field procedures Troubleshoot and locate common PV array and system faults using appropriate methodologies and testing tools
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Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00
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Course Curriculum Unit 01: Introduction Welcome 00:02:00 Unit 02: Excel Productivity Tips -Part 1 Camera Tool 00:05:00 Add Line Break in Formula Bar 00:03:00 Advanced Copy-Paste using Office Clipboard 00:03:00 Navigation between Worksheets using Shortcut Keys 00:01:00 Flash Fill 00:02:00 Add Multiple Rows and Columns Quickly 00:02:00 Delete Blank Rows 00:03:00 Multi Level Row and Column Sorting 00:04:00 Add Sparklines 00:03:00 Paste Special - Transpose 00:03:00 Unit 03: Excel Productivity Tips - Part 2 Snap to Grid 00:03:00 Create Custom Auto fill List 00:06:00 Absolute Cell Reference 00:03:00 Import Data from Web page 00:04:00 Move Cell Direction 00:03:00 Delete Data using Mouse 00:02:00 Status Bar Quick Calculations 00:03:00 Link Text Boxes to Cell 00:04:00 Phone Number and ZIP Code Format 00:04:00 Speaking Cell 00:05:00 Unit 04: Excel Productivity Tips - Part 3 Invisible Text 00:03:00 Worksheet Grouping 00:04:00 Advanced Transpose 00:04:00 XLStart Folder 00:03:00 Use Slicers 00:05:00 Convert Text to Numbers 00:03:00 Hiding Workbook Elements 00:02:00 Useful Shortcut Keys 00:03:00 Sort data from Left to Right 00:03:00 Advanced Filter (Complex) 00:11:00 Unit 05: Excel Productivity Tips - Part 4 Email as PDF 00:02:00 Synchronous Scrolling 00:03:00 Quick Analysis of data within Excel 00:02:00 Fill blank cells with Value 00:03:00 Hidden Chart Source Data 00:03:00 Two more Shortcuts 00:03:00 Add Blank Rows 00:03:00 Custom views in Excel 00:06:00 EMBED Feature 00:04:00 Adding Country code in Mobile Numbers 00:04:00 Unit 05: Excel Productivity Tips - Part 5 Plot an Average Line to a Chart 00:04:00 3D Referencing 00:04:00 Extract Unique Values 00:03:00 Excel Array Formula 00:04:00 Forecast Sheet 00:04:00 Add Spin Controls in Excel 00:05:00 Move Data using Mouse 00:01:00 Add new entry in Auto Correct to use across Office Applications 00:05:00 Find Differences between Two Lists 00:02:00 Find formulas Quickly 00:02:00 Unit: 06 Wrap Up Thank You 00:01:00
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Overview This comprehensive course on Understand Piping & Instrumentation Diagrams P&IDs will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Understand Piping & Instrumentation Diagrams P&IDs comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Understand Piping & Instrumentation Diagrams P&IDs. It is available to all students, of all academic backgrounds. Requirements Our Understand Piping & Instrumentation Diagrams P&IDs is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 14 sections • 119 lectures • 08:26:00 total length •Introduction: 00:04:00 •What's a P&ID ?: 00:03:00 •Why is a P&ID so important ?: 00:02:00 •Who uses P&ID's ?: 00:06:00 •How do P&ID's look like ?: 00:08:00 •Introduction- PID READING: 00:02:00 •Anatomy of a P&ID: 00:01:00 •The title block: 00:03:00 •The drawing scale: 00:03:00 •The grid system: 00:02:00 •The revision block: 00:03:00 •Changes: 00:02:00 •Notes and legends: 00:03:00 •Valve symbols: 00:14:00 •Valve actuator symbols: 00:09:00 •Control valve designations: 00:02:00 •Standards and conventions for valve status: 00:07:00 •Process equipment symbols: 00:12:00 •Piping symbols: 00:03:00 •Pipe fitting symbols: 00:03:00 •Isolating, venting & draining symbols for ease of maintenance: 00:05:00 •Instrumentation: 00:03:00 •Sensing devices and detectors: 00:04:00 •Location symbols: 00:04:00 •Modifiers and transmitters: 00:05:00 •Indicators and recorders: 00:03:00 •Controllers: 00:03:00 •Example #1 : Identifying process equipment and flow paths: 00:05:00 •Example #2 : Identifying valve position and failure mode: 00:03:00 •Example #3 : Identifying the symbols: 00:02:00 •Piping designation code: 00:06:00 •Equipment designation code: 00:03:00 •Instrument designation code: 00:02:00 •Miscellaneous designation codes: 00:02:00 •The process: 00:01:00 •Process control: 00:06:00 •The control loop: 00:02:00 •Process control terms: 00:10:00 •Control loops : Feedback control: 00:02:00 •Pressure control loops: 00:01:00 •Flow control loops: 00:01:00 •Level control loops: 00:01:00 •Temperature control loops: 00:01:00 •Multi-variable loops: 00:02:00 •Feedforward control: 00:02:00 •Feedforward + Feedback: 00:01:00 •Cascade control: 00:08:00 •Split range control: 00:03:00 •Operations on control signals: 00:02:00 •Ratio control: 00:02:00 •Batch control: 00:01:00 •Selective control: 00:01:00 •Do we need to control at all ?: 00:01:00 •Principles of equipment-wise control: 00:10:00 •Pipe control system: 00:02:00 •Control of a single pipe: 00:02:00 •Control of pressure in a pipe: 00:03:00 •Control of flow in a pipe: 00:04:00 •Flow merging: 00:08:00 •Flow splitting: 00:05:00 •Centrifugal pump control: 00:04:00 •Control valve vs Variable Frequency Drive (VFD) for centrifugal pumps: 00:03:00 •Minimum flow control for centrifugal pumps: 00:09:00 •Positive displacement pump control: 00:02:00 •Control by a recirculation pipe for PD pumps: 00:03:00 •Variable Speed Drive (VSD) control for PD pumps: 00:01:00 •Control by stroke adjustment for PD pumps: 00:01:00 •Compressor control system: 00:02:00 •Compressor capacity control: 00:12:00 •Compressor anti-surge control: 00:03:00 •Heat transfer equipment control: 00:02:00 •Heat exchanger direct control system: 00:04:00 •Heat exchanger bypass control system: 00:04:00 •Reactor temperature control: 00:06:00 •Air cooler control: 00:02:00 •Heat exchanger for heat recovery: 00:01:00 •Heat exchanger back pressure control: 00:02:00 •Basic fired heater control: 00:08:00 •Complex fired heater control: 00:05:00 •Container and vessel control: 00:07:00 •Container blanket gas control: 00:02:00 •Safety strategies: 00:01:00 •Concept of Safety Instrumented Systems (SIS): 00:01:00 •SIS actions and types: 00:14:00 •SIS extent: 00:02:00 •SIS requirement: 00:03:00 •Anatomy of a SIS: 00:02:00 •SIS element symbols: 00:01:00 •SIS primary elements : Sensors: 00:03:00 •SIS final elements: 00:04:00 •Switching valve actuator arrangements: 00:02:00 •Valve position validation: 00:02:00 •Merging a switching valve and a control valve: 00:03:00 •SIS logics: 00:01:00 •Showing safety instrumented functions on P&ID's: 00:07:00 •Discrete control: 00:05:00 •Alarm system: 00:02:00 •Anatomy of alarm systems: 00:02:00 •Alarm requirements: 00:06:00 •Alarm system symbology in P&ID's: 00:06:00 •Concept of common alarms: 00:01:00 •Fire and Gas Detection Systems (FGS): 00:03:00 •Electric motor control: 00:07:00 •P&ID representation of commands and responses: 00:05:00 •P&ID representation of inspection and repair: 00:05:00 •P&ID example of electro-motor control: 00:04:00 •P&ID example #1 : Legend and specifications: 00:05:00 •P&ID example #2 : Hydrogen delivery station: 00:16:00 •P&ID example #3 : Acid system: 00:13:00 •P&ID example #4 : Centrifugal pump: 00:09:00 •P&ID example #5 : Utility station: 00:04:00 •P&ID example #6 : Waste water filter: 00:08:00 •P&ID example #7 : Steam separator: 00:15:00 •P&ID example #8 : Flare knock-out drum: 00:14:00 •P&ID example #9 : Centrifugal compressor: 00:05:00 •P&ID example #10 : Hydrogen production from shale gas: 00:11:00 •P&ID example #11 : Fired heater: 00:07:00 •Resources - Understand Piping & Instrumentation Diagrams P&IDs: 00:00:00 •Assignment - Understand Piping & Instrumentation Diagrams P&IDs: 00:00:00
A collection of my most popular courses and webinars to help you figure out how best to manage your fatigue challenge and move forwards towards a better level of wellness. Help for all stages of your journey - from the initial basics, to returning to work and figuring out when it's time to incorporate more movement and exercise. It also contains a webinar to share with your loved ones, so that they can better understand what you're going through. Contents £10 Communicating with others when you've got fatigue Course 4 Lessons Fatigue journeys vary from person to person - no two experiences are the same. But there's one challenging topic that seems to feature in most people's journeys at one time or another... communication! In this webinar recording I share tips and advice on how to tackle five of the most common conversation challenges when you're on a fatigue recovery journey. View product £75 Fatigue Reset: Crack pacing once and for all Course 32 Lessons View product £10 How to achieve a successful return to work Course 1 Lesson If you’ve had to take time off from your job for months or even years, contemplating a return to work can be difficult. How do you know if you’re ready? Are you well enough to return full-time or do you need to negotiate a phased approach? And what can you do to make sure the return itself goes as successfully as possible? This webinar starts to answer those questions - and many more! View product £10 How to cope better with fatigue Course 2 Lessons A recording of a live webinar held in November 2023. I share the most important areas that you should be focussing on, so that you minimise the time spent wondering what on earth you can do to improve your fatigue challenge and current situation - and get onto the right path to recovery. View product £10 How to start exercising when you have fatigue Course 3 Lessons We hear how helpful it is to exercise for health and wellbeing. But when you have fatigue it can be difficult to know if this is going to help or hinder. When *is* it the right time to start to feel confident about moving more and starting to exercise?In this webinar recording I share tips and advice on how to tackle five of the most common conversation challenges when you're on a fatigue recovery journey. View product £10 When a Loved One has fatigue...how to help them, and yourself. Course 5 Lessons A fatigue-related condition doesn’t only impact the life of the person who's ill, it often changes things for you, their loved ones. Adjusting to this can be tough for you, and it can be difficult to know how to best help them.This webinar will increase your understanding of what life feels like for your loved one, and help you know how to support them on their recovery journey, while looking after yourself too.View product