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Duration 2.25 Days 13.5 CPD hours This course is intended for The job roles best suited to the material in this course are: sales personnel, accountants, administrators, auditors, lab assistants, office job positions. Overview Work with functions. Work with lists. Analyze data. Visualize data with charts. Use PivotTables and PivotCharts. Work with multiple worksheets and workbooks. Share and protect workbooks. Automate workbook functionality. Use Lookup functions and formula auditing. Forecast data. Create sparklines and map data This course provides the knowledge to create advanced workbooks and worksheets that can deepen the understanding of organizational intelligence. The ability to analyze massive amounts of data, extract actionable information from it and present that information to decision makers. In addition this course will give you the ability to collaborate with colleagues, automate complex or repetitive tasks and use conditional logic to construct and apply elaborate formulas and functions which will allow you to work through a lot of data and generate the answers that your organisation needs. WORKING WITH FUNCTIONS Topic A: Work with Ranges Topic B: Use Specialized Functions Topic C: Work with Logical Functions Topic D: Work with Date and Time Functions Topic E: Work with Text Functions WORKING WITH LISTS Topic A: Sort Data Topic B: Filter Data Topic C: Query Data with Database Functions Topic D: Outline and Subtotal Data ANALYZING DATA Topic A: Create and Modify Tables Topic B: Apply Intermediate Conditional Formatting Topic C: Apply Advanced Conditional Formatting VISUALIZING DATA WITH CHARTS Topic A: Create Charts Topic B: Modify and Format Charts Topic C: Use Advanced Chart Features USING PIVOTTABLES AND PIVOTCHARTS Topic A: Create a PivotTable Topic B: Analyze PivotTable Data Topic C: Present Data with PivotCharts Topic D: Filter Data by Using Timelines and Slicers WORKING WITH MULTIPLE WORKSHEETS AND WORKBOOKS Topic A: Use Links and External References Topic B: Use 3-D References Topic C: Consolidate Data SHARING AND PROTECTING WORKBOOKS Topic A: Collaborate on a Workbook Topic B: Protect Worksheets and Workbooks AUTOMATING WORKBOOK FUNCTIONALITY Topic A: Apply Data Validation Topic B: Search for Invalid Data and Formulas with Errors Topic C: Work with Macros USING LOOKUP FUNCTIONS AND FORMULAS AUDITING Topic A: Use Lookup Functions Topic B: Trace Cells Topic C: Watch and Evaluate Formulas FORECASTING DATA Topic A: Determine Potential Outcomes Using Data Tables Topic B: Determine Potential Outcomes Using Scenarios Topic C: Use the Goal Seek Feature Topic D: Forecast Data Trends CREATING SPARKLINES AND MAPPING DATA Topic A: Create Sparklines Topic B: Map Data

Description: Scope and Requirement skill help you to develop the good understanding of project requirement. In the Scope & Requirements Training - Complete Video Course, you will learn the appropriate knowledge for increasing your scope and requirements. The Scope & Requirements Training - Complete Video Course includes the proper definition of scope, the ways of developing effective work breakdown structures, the requirement basics, the testable requirements, business domain modelling, and the Software Requirements Specifications. Throughout the Scope & Requirements Training - Complete Video Course, you will also learn the effective communication methods that are used for Project Management. You will learn the proper communication skill and listening skills so that you can use these two receptive skills for the growth of your business. The purpose of the course is to create more opportunities for your business. At the end of the course, you will know the essential tools and techniques for Project Requirements. 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? Scope & Requirements Training - 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 Scope & Requirements Training - 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. Effective Listening Skills for Requirements Definition Listening FREE 00:09:00 Communication 00:09:00 To Be More Effective 00:19:00 Stakeholders Stakeholders 00:05:00 Stakeholder Questions 00:08:00 Scope Definition Scope Definition 00:15:00 Solution Assessment & Validation 00:13:00 The Project Data Sheet (PDS) 00:17:00 Creating Effective Work Breakdown Structures Creating Effective Work Breakdown Structures 00:08:00 Components of the WBS 00:13:00 Answer Four Key Questions 00:12:00 Requirements Basics Requirements Basics 00:05:00 What Makes A Good Requirement 00:10:00 Requirements 00:06:00 Use Cases Use Cases 00:07:00 Process for Developing a Use Case 00:04:00 Development Methodologies Development Methodologies 00:21:00 Rational Unified Process 00:14:00 The Scrum Flow 00:22:00 Testable Requirements Testable Requirements 00:09:00 Ambiguity Review 00:06:00 The Software Requirements Specification (SRS) The SRS 00:06:00 Quality Measures Related To Individual SRS 00:05:00 Business Domain Modeling Business Domain Modeling 00:05:00 BDM Example 00:06:00 Database Tables 00:03:00 Other Advanced Tools Other Advanced Tools 00:13:00 BlockSwimlane Workflow Diagram 00:13:00 Class Diagrams 00:11:00 Mock Exam Mock Exam- Scope & Requirements Training - Complete Video Course 00:20:00 Final Exam Final Exam- Scope & Requirements Training - Complete Video Course 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Master Go programming with an in-depth course covering advanced topics such as authentication, authorization, JWT tokens, and refresh tokens. Learn how to write reliable code with effective unit testing techniques, while exploring concepts such as logging, error handling, and modularization. Build secure and scalable web applications with Go to take your coding expertise to the next level.

This Access 2016 Intermediate is specially designed for you if you are thinking to take your Microsoft Access skills to the next level. Through the course, you'll master more advanced techniques for this powerful database program and build an entire database project from scratch.  From building reports to using conditional formatting, you'll see how to present your data and gain techniques for using Visual Basic to automate common tasks. You will learn to design tables for improved accuracy in data entry by setting default values and restricting data entry, review the various options to share data with other applications, including Word and Excel, learn about Action Queries to automate updating, appending and deleting table data, and review various advanced query techniques such as using Query Joins, Parameter queries, working with totals and Crosstab queries. Finally, you'll build a navigation form to make it easy for your users to find their way around your database.  What Will I Learn? Design Tables for Better Data Entry Share Data with Other Applications Work with Action Queries Advanced Query Techniques Automate Processes with Macros Advanced Forms Advanced Report Techniques Requirements Access 2016 Introduction or equivalent experience. Who is the target audience? Students who want to take Access to the next level and improve their database design skills. Introduction Introduction FREE 00:01:00 Designing Tables for Better Data Entry Reviewing Table Design Principles 00:04:00 Setting Field Size, Formats and Captions 00:06:00 Setting Default Value and Required Fields 00:03:00 Restricting Data Entry Using Data Validation 00:02:00 Restricting Data Entry Using Input Masks 00:06:00 Sharing Data with Other Applications Exporting Tables and Queries to Excel 00:03:00 Importing Data from a TXT File 00:03:00 Importing Data from Excel 00:02:00 Exporting Data to a TXT File 00:02:00 Linking External Data Sources 00:03:00 Using Word Merge 00:02:00 Working with Action Queries What are Action Queries 00:02:00 Creating an Update Query 00:02:00 Creating an Append Query 00:03:00 Creating a Delete Query 00:02:00 Creating a Make Table Query 00:02:00 Changing the Start Number of an Auto Number Field 00:03:00 Advanced Query Techniques Creating Query Joins 00:05:00 Creating Find Unmatached and Find Duplicate Queries 00:03:00 Creating Parameter Queries 00:04:00 Using -Like- Keyword in Parameter Queries 00:02:00 Creating a Top X Query 00:02:00 Reviewing Calculated Query Fields 00:03:00 Summarizing Query Data with Totals 00:03:00 Inserting Where Statements in Summary Queries 00:01:00 Creating a Crosstab Query 00:03:00 Automating Processes with Macros Understanding Macro Basics 00:06:00 Creating Macros to Open Forms by Record 00:04:00 Validating Data Entry with Macros 00:04:00 Creating a Macro to Automate Data Entry 00:03:00 Advanced Data Entry Using Macros and DLOOKUP Function 00:06:00 Advanced Form Using Conditional Formatting 00:02:00 Organizing Form Fields with Tab Controls 00:03:00 Creating a Combo Box Control 00:02:00 Creating an Option Group Control 00:03:00 Using a Subform to Show Data from a Related Table 00:03:00 Advanced Report Techniques Inserting a Chart on a Report 00:03:00 Showing Data in Columns 00:02:00 Inserting a Subreport 00:02:00 Configuring Reports with Parameter Queries 00:04:00 Sending Reports 00:02:00 Conclusion Course Recap 00:01:00 Resources Resources - Access 2016 Intermediate 00:00:00 Course Certification

Master Angular and Dart (AngularDart) and build high-performance, flexible, and dynamic web apps

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Welcome to a brand-new course, where you can learn how to create modern and beautiful web projects and templates; if you want to develop and customize your portfolio, become an experienced developer, then this is the right course for you. Level-up your HTML, CSS, and JavaScript coding skills with this course.

Duration 2 Days 12 CPD hours This course is intended for This course is designed for students wishing to gain intermediate-level skills or individuals whose job responsibilities include constructing relational databases and developing tables, queries, forms, and reports in Microsoft Access for Office 365. Overview In this course, you will optimize an Access database. You will: Provide input validation features to promote the entry of quality data into a database. Organize a database for efficiency and performance, and to maintain data integrity. Improve the usability of Access tables. Create advanced queries to join and summarize data. Use advanced formatting and controls to improve form presentation. Use advanced formatting and calculated fields to improve reports. In this course, you will expand your knowledge of relational database design; promote quality input from users; improve database efficiency and promote data integrity; and implement advanced features in tables, queries, forms, and reports. Extending your knowledge of Access will result in a robust, functional database for your users.This course covers Microsoft Office Specialist Program exam objectives to help you prepare for the Access Expert (Office 365 and Office 2019): Exam MO-500 certification. Improving Table Usability Topic A: Create Lookups Within a Table Topic B: Work with Subdatasheets Creating Advanced Queries Topic A: Create Query Joins Topic B: Create Subqueries Topic C: Summarize Data Improving Form Presentation Topic A: Apply Conditional Formatting Topic B: Create Tab Pages with Subforms and Other Controls Creating Advanced Reports Topic A: Apply Advanced Formatting to a Report Topic B: Add a Calculated Field to a Report Topic C: Control Pagination and Print Quality Topic D: Add a Chart to a Report Importing and Exporting Table Data Topic A: Import and Link Data Topic B: Export Data Topic C: Create a Mail Merge Using Queries to Manage Data Topic A: Create Action Queries Topic B: Create Unmatched and Duplicate Queries Creating Complex Reports and Forms Topic A: Create Subreports Topic B: Create a Navigation Form Topic C: Show Details in Subforms and Popup Forms Creating Access Macros Topic A: Create a Standalone Macro to Automate Repetitive Tasks Topic B: Create a Macro to Program a User Interface Component Topic C: Filter Records by Using a Condition Topic D: Create a Data Macro Using VBA to Extend Database Capabilities Topic A: Introduction to VBA Topic B: Using VBA with Form Controls Managing a Database Topic A: Back Up a Database Topic B: Manage Performance Issues Topic C: Document a Database Distributing and Securing a Database Topic A: Split a Database for Multiple-User Access Topic B: Implement Security Topic C: Convert an Access Database to an ACCDE File Topic D: Package a Database with a Digital Signature

Description Register on the Deep Learning & Neural Networks Python - Keras today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The Deep Learning & Neural Networks Python - Keras course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content Course Introduction And Table Of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML Or DL For The Next AI Project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation And Sample Program To Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow Library Installation And Sample Program To Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation And Switching Theano And TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps And Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network With Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training And Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding The Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - K-Fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing The Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding The Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing The Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning For Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding The Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing The Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement By Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement By Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement By Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load The Trained Model As JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save And Load Model As YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load And Predict Using The Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load And Predict Using The Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load And Predict Using The Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load And Predict Using The Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction To Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading The Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule Using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Handwritten Digit Recognition Dataset MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model Using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN Using MNIST Large CNN using MNIST 00:09:00 Load And Predict Using The MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction To Image Augmentation Using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation Using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation Using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation Using Rotation And Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding And Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN Using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train And Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load And Predict Using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00