5816 Computing courses in Gerrards Cross delivered Online

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Test-Driven Development - A Stunningly Quick Introduction "The job of QA is not just to do testing it's to build quality in.How often have you heard that sentence? And how often has it been followed up with solid practices for actually building quality in? Test-Driven Development (TDD) is one of the foundational practices of high-quality product development. Popularized nearly 20 years ago, TDD is an important skill for high-quality software development. If you want it to be easier to build high-quality code, then you need to understand TDD. In this hands-on session, we'll learn by doing. Richard will facilitate a coding dojo, a safe place to learn and practice the skills of test-driven development. We'll mob-program together on a coding kata - an easy programming problem - to learn TDD, refactoring, clean code, code smells, and more - all in the pursuit of technical agility, business agility, and a great product that people love. To follow along, bring your laptop and development environment. You'll leave with an introduction to solid new skills, including: Test-driven development (TDD) Extreme Programming (XP) Refactoring and refactoring patterns Code smells Mob programming

Overview of Clinical Coding Join our Clinical Coding course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Clinical Coding course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Clinical Coding course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! Get a Quick Look at The Course Content: This Clinical Coding Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. 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 Clinical Coding. 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 Clinical Coding 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 Clinical Coding 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 Clinical Coding 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 Clinical Coding 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 Module 01: Introduction to Clinical Coding Introduction to Clinical Coding 00:44:00 Module 02: Introduction to Clinical Records Its Confidentiality Introduction to Clinical Records and Its Confidentiality 00:51:00 Module 03: Clinical Terminology and Jargons Clinical Terminology and Jargons 00:44:00 Module 04: Introduction to ICD-10 Coding Introduction to ICD-10 Coding 00:34:00 Module 05: General Coding Standards of ICD-10 General Coding Standards of ICD-10 00:44:00 Module 06: ICD-10 5th Edition Codes (Chapter 1 to 4) ICD-10 5th Edition Codes (Chapter 1 to 4) 00:46:00 Module 07: ICD-10 5th Edition Codes (Chapter 5 to 10) ICD-10 5th Edition Codes (Chapter 5 to 10) 01:02:00 Module 08: ICD-10 5th Edition Codes (Chapter 11 to 15) ICD-10 5th Edition Codes (Chapter 11 to 15) 01:00:00 Module 09: ICD-10 5th Edition Codes (Chapter 16 to 22) ICD-10 5th Edition Codes (Chapter 16 to 22) 01:04:00 Module 10: Introduction to OPCS-4 Introduction to OPCS-4 00:48:00 Module 11: Introduction to SNOMED CT Introduction to SNOMED CT 00:41:00 Module 12: Other types of Clinical Coding Other types of Clinical Coding 00:34:00 Module 13: Legal and Ethical Aspects of Working in a Clinical Environment Legal and Ethical Aspects of Working in a Clinical Environment 00:35:00 Assignment Assignment - Clinical Coding 00:00:00

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Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. 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

Description: This Microsoft Office 2013 PowerPoint Advanced - Complete Video Course covers more advanced features of PowerPoint 2013. In this series, you will learn how to modify the PowerPoint environment, using methods like customizing design templates, working with media and animations, and adding SmartArt to a presentation, customizing a slide show and securing and distributing a presentation, use tables and spreadsheets to display data in a presentation, learn how to add, format and edit charts with the chart tools and quick clicks, design slide masters and apply slide transitions, apply animations to images in a slide show and edit the timing, add videos to a PowerPoint presentation and trim the media, practice delivering presentations with the presenter's tools, use the review tools to proof and protect presentations, and more. If, you have the basic skills with Microsoft Office 2013 PowerPoint and want to learn advanced-level skills then this course will be perfect for you. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Microsoft Office 2013 PowerPoint Advanced - Complete Video Course is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Microsoft Office 2013 PowerPoint Advanced - Complete Video Course is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Modifying the PowerPoint Environment Customize the User Interface FREE 00:12:00 Set PowerPoint 2013 Options 00:04:00 Customizing Design Templates Modify Slide Masters and Slide Layouts 00:12:00 Add Headers and Footers 00:06:00 Modify the Notes Master and the Handout Master 00:04:00 Adding SmartArt to a Presentation Create SmartArt 00:06:00 Modify SmartArt 00:07:00 Working with Media and Animations Add Audio to a Presentation 00:13:00 Add Video to a Presentation 00:12:00 Customize Animations and Transitions 00:14:00 Collaborating on a Presentation Review a Presentation 00:18:00 Store and Share Presentations on the Web 00:11:00 Customizing a Slide Show Annotate a Presentation 00:04:00 Set Up a Slide Show 00:04:00 Create a Custom Slide Show 00:04:00 Add Hyperlinks and Action Buttons 00:10:00 Record a Presentation 00:07:00 Securing and Distributing a Presentation Secure a Presentation 00:09:00 Broadcast a Slide Show 00:08:00 Create a Video or a CD 00:09:00 Mock Exam Mock Exam- Microsoft Office 2013 PowerPoint Advanced - Complete Video Course 00:20:00 Final Exam Final Exam- Microsoft Office 2013 PowerPoint Advanced - Complete Video Course 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Description Do you want to know how to be an expert in creating forms and gathering data? Are you looking for the easiest method regarding MS InfoPath? You may look at the MS InfoPath 2013: Working With InfoPath 2013 in SharePoint course. This course may assist you to get an approximate idea about this field. The MS InfoPath 2013: Working With InfoPath 2013 in SharePoint course incorporates some basic ideas regarding the use of MS InfoPath. It enables to know you how to make forms and collect data by using Infopath within SharePoint. It also teaches you how to edit, create, and publish a form along with a strong command of associated properties. It gives you a proper direction to use Infopath forms by utilizing WebParts. After the end of the course, you will be an expert on some advanced functions of InfoPath that enables you to modify data source and work with it vivid sections. Assessment: This course does not involve any MCQ test. Students need to answer assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Once the answers are submitted, the instructor will check and assess the work. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? MS InfoPath 2013: Working With InfoPath 2013 in SharePoint is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our MS InfoPath 2013: Working With InfoPath 2013 in SharePoint is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Introduction Introduction FREE 00:01:00 SharePoint and InfoPath Using InfoPath with SharePoint 00:04:00 Exploring the InfoPath Interface 00:03:00 Creating a Form from an Existing List 00:03:00 Creating a new List and Form within InfoPath 00:04:00 Creating a Form in InfoPath Using SharePoint Designer 00:02:00 Editing a Form 00:02:00 Publishing a Form 00:02:00 Restoring the Default SharePoint Form 00:03:00 Working with List Forms Components of the InfoPath Form 00:03:00 Formatting Text in the Form 00:03:00 Spellcheck Your Form 00:02:00 Inserting or Deleting a Table 00:02:00 Formatting a Table 00:03:00 Add or Remove Rows and Columns 00:02:00 Merging and Splitting Cells 00:04:00 Adding or Removing a Field 00:03:00 Resizing and Formatting a Field 00:03:00 Changing Field Controls 00:05:00 Inserting a Section 00:03:00 Inserting a Picture 00:02:00 Inserting a Button 00:05:00 Inserting a Calculated Value 00:04:00 Setting Default Field Values 00:05:00 Creating a Validation Rule 00:04:00 Creating a Formatting Rule 00:04:00 Creating an Action Rule 00:05:00 Modifying or Deleting a Rule 00:02:00 Setting the Form Load Rules 00:03:00 Advanced InfoPath Features Exploring the Fields Pane 00:02:00 Creating a Data Source 00:05:00 Modifying and Deleting a Data Source 00:02:00 Creating a View 00:03:00 Configuring View Settings 00:03:00 Creating Cascading Columns 00:06:00 Understanding Repeating Sections and Tables 00:03:00 Creating a Repeating Section 00:04:00 Using Repeating Tables to Add Multiple Items to a List 00:08:00 Using Repeating Sections to Show Existings Records 00:07:00 Hiding a Form Section Based on Field Values 00:05:00 InfoPath Forms Within SharePoint Using the InfoPath Form WebPart on a SP Page 00:04:00 Using Form Views for Different Groups 00:06:00 InfoPath Form WebPart and WebPart Filters 00:08:00 Conclusion Course Recap 00:01:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

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Discover the transformative power of ITIL Practitioner in just one course! Unleash your potential in IT Service Management, master principles and themes, embrace organizational change, and unlock the secrets of continual improvement. Join us on a journey to IT excellence.