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Microsoft Excel training | Excel Courses for Accountants: Excel Courses Overview Microsoft Excel is the world's most popular spreadsheet program, learning how to use the software with Osborne Training shows that you've taken one of the best Excel training courses available. Comprehensive excel courses come with up to date material to practice at home and during your class. Excel courses for accountants This course is a highly recognised excel course for accountants. We will also provide a step by step manual of all the tricks you can do using Excel spreadsheets to gain better management reporting and budgeting skills. It is a fundamental program for professional Accountants. Excel spreadsheets are the most powerful tool, extensively used for reporting and analysis. Having advanced skills in excel can excel your career and help you to stand ahead of the competitive job market. Advanced skills in Excel is a must for any potential professional accountants and who are already running a practice or considering opening a practice. Certificate of Attendance Excel Course Content Creating worksheets, formatting text Simple and complex formulas Handling rows and columns Average, max and min functions and using charts. Use of IF Formula Summing Techniques Cell References Formula Linking Tables and Bordering Look up References (Vlookup, Hlookup, etc) Data Validation Conditional Formatting Date & Time Formulas Charts & Graphs Protection & Security Creating Pivot Table Pivot Table Analysis

Master frontend web development using HTML, CSS, CSS Flexbox, CSS Grid, and JavaScript

The future of fitness is here. Be a part of it. The NASM Virtual Coaching Specialization’s immersive online experience will equip you with the skills, tools, and strategies necessary to launch, operate, or transition your current fitness or wellness business to a successful online coaching business. By doing so, you’ll open yourself to a whole new world of opportunities. You’ll also be able to help clients from around the world anywhere and anytime. It’s the ultimate flexibility as a trainer while also creating new revenue streams. As part of this specialization, you will learn the skills and knowledge necessary to conduct and modify fitness assessments online, how to cue clients in an online environment, how to run your business digitally, effective sales and marketing strategies, and much more!

This course is designed to guide you through Selenium WebDriver and Java, right from the basic to the advanced aspects. Loaded with exercises and examples, this course provides an interactive learning experience.

The Microsoft Access 2016 Beginner to Advanced course is a comprehensive training program covering all levels of proficiency. From creating simple databases to advanced querying, form creation, report generation, and database management, this course provides a deep understanding of Microsoft Access's features and functions. Learning Outcomes: Build and modify Access databases, tables, and fields. Create effective queries to sort, filter, and summarize data. Develop professional-looking reports with controls, charts, and calculations. Design forms with controls, tab pages, and conditional formatting. Automate tasks using macros and understand the basics of VBA. Manage database performance, security, and object dependencies. Create a database switchboard and modify startup options. Understand data normalization, table relationships, and import/export processes. Why buy this Microsoft Access 2016 Beginner to Advanced? Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Microsoft Access 2016 Beginner to Advanced you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? Beginners with no previous experience in Microsoft Access. Professionals seeking to enhance their database management and reporting skills. Individuals aiming to become proficient in creating and maintaining databases. Students pursuing careers in data analysis, administration, or database management. Prerequisites This Microsoft Access 2016 Beginner to Advanced was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Analyst: Analyze, interpret, and present data insights using Access. Database Administrator: Design, implement, and maintain databases for organizations. Administrative Assistant: Manage data, generate reports, and streamline processes. Project Manager: Organize project-related data and create performance reports. Business Owner: Build and manage databases to support business operations. Course Curriculum Module - 1 Orientation to Microsoft Access 01:00:00 Create a Simple Access Database 01:00:00 Get Help in Microsoft Access 00:30:00 Modify Table Data 00:30:00 Work with Records 01:00:00 Sort and Filter Records 00:30:00 Create Lookups 01:00:00 Join Data from Different Tables in a Query 01:00:00 Sort and Filter Data in a Query 01:00:00 Perform Calculations in a Query 00:30:00 Create Parameter Queries 00:30:00 Create Action Queries 00:30:00 Create Find Duplicate and Find Unmatched Queries 00:30:00 Summarize Data 00:30:00 Create a Report 01:00:00 Add Controls to a Report 00:30:00 Enhance the Appearance of a Report 00:30:00 Prepare a Report for Print 00:30:00 The Access Options Dialog Box 01:00:00 Relational Database Design 00:30:00 Create a Table 01:00:00 Modify a Table and Fields 00:30:00 Create Table Relationships 00:30:00 Create Query Joins 00:30:00 Join Tables That Have No Common Fields 00:30:00 Relate Data within a Table 00:30:00 Work with Subdatasheets 00:30:00 Create Subqueries 00:30:00 Data Normalization 01:00:00 Create a Junction Table 00:30:00 Import Data into Access 00:30:00 Export Data to Text File Formats 00:30:00 Export Access Data to Excel 00:30:00 Create a Mail Merge 00:30:00 Organize Report Information 00:30:00 Format Reports 00:30:00 Include Charts in a Report 00:30:00 Add a Calculated Field to a Report 00:30:00 Add a Subreport to an Existing Report 00:30:00 Create a Mailing Label Report 00:30:00 Publish a Report as PDF 00:30:00 Activities - Microsoft Access 2016 for Beginners 00:00:00 Module - 2 Add Controls to Forms 01:00:00 Set Form Controls 01:00:00 Create Subforms 00:30:00 Organize Information with Tab Pages 00:30:00 Enhance Navigation with Forms 00:30:00 Format a Form 01:00:00 Apply Conditional Formatting 00:30:00 Field Validation 00:30:00 Form and Record Validation 00:30:00 Create a Macro 01:00:00 Restrict Records Using a Condition 00:30:00 Validate Data Using a Macro 00:30:00 Automate Data Entry Using a Macro 00:30:00 Convert a Macro to VBA 00:30:00 Link Tables to External Data Sources 00:30:00 Manage a Database 00:30:00 Determine Object Dependency 00:30:00 Document a Database 00:30:00 Analyze the Performance of a Database 00:30:00 Split a Database for Multiple User Access 00:30:00 Implement Security 00:30:00 Set Passwords 00:30:00 Convert an Access Database to an ACCDE File 00:30:00 Package a Database with a Digital Signature 00:30:00 Create a Database Switchboard 01:00:00 Modify a Database Switchboard 00:30:00 Set Startup Options 00:30:00 Activities - Microsoft Access 2016 Advanced 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python 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? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Learn about the jQuery library from scratch and stretch your journey from a beginner-level to advanced-level professional with a step-by-step and comprehensive course. A basic understanding of the JavaScript Document Object Model and CSS is suggested as a prerequisite to this course.

Get started with creating JavaFX applications using TornadoFX - A lightweight JavaFX framework for Kotlin

Learning Objectives Introduction , Customizing Excel , Analyzing Data with Logical Functions , Working with Lookup Functions , Using Text Functions , Working with Date and Time Functions , Formula Auditing , What-If Analysis , Worksheet and Workbook Protection , Automating with Macros , Working with Form Controls , Ensuring Data Integrity , Collaborating in Excel , Importing and Exporting Data to a Text File , Conclusion   Pre-Requisites Excel 365 Introduction and Intermediate courses or equivalent experience.   Description This course will teach students advanced concepts and formulas in Microsoft Excel 365. Students will learn functions such as SUMIF, AVERAGEIF, and COUNTIF, advanced lookup functions, and complex logical and text functions. Additionally, students will experiment with auditing formulas and error checking, use the What-If Analysis tools, learn the options for worksheet and workbook protection, review advanced use of PivotTables and PowerPivot add-in, work with Macros, use form controls, and ensure data integrity in their worksheets and workbooks. Students will also learn about Excel's many collaboration features and import and export data to and from their workbooks. Course Introduction Introduction 00:01:00 Section 01 Lesson 01-Customizing the Ribbon 00:09:00 Lesson 02-Customizing the Quick Access Toolbar 00:06:00 Lesson 03-Customizing the General and Formula Options 00:04:00 Lesson 04-Customizing the AutoCorrect Options 00:03:00 Lesson 05-Customizing the Save Defaults 00:04:00 Lesson 06-Customizing Advanced Excel Options 00:03:00 Section 02 Lesson 01-Working with the Most Common Logical Functions 00:03:00 Lesson 02-Understanding IF Functions 00:06:00 Lesson 03-Evaluating Data with the AND Function 00:05:00 Lesson 04-Evaluating Data with the OR Function 00:03:00 Lesson 05-Creating a Nested IF Function 00:05:00 Lesson 06-Using the IFS Function 00:03:00 Lesson 07-Summarizing Data with SUMIF 00:03:00 Lesson 08-Summarizing Data with AVERAGEIF 00:02:00 Lesson 09-Summarizing Data with COUNTIF 00:02:00 Lesson 10-Summarizing Data with MAXIFS and MINIFS 00:03:00 Lesson 11-Using the IFERROR Function 00:03:00 Section 03 Lesson 01-What are Lookup Functions 00:03:00 Lesson 02-Using VLOOKUP 00:08:00 Lesson 03-Using HLOOKUP 00:03:00 Lesson 04-Using VLOOKUP with TRUE 00:04:00 Lesson 05-Using HLOOKUP with TRUE 00:02:00 Lesson 06-Using the Index Function 00:03:00 Lesson 07-Using the MATCH Function 00:03:00 Lesson 08-Combining INDEX and MATCH 00:04:00 Lesson 09-Comparing Two Lists with VLOOKUP 00:02:00 Lesson 10-Comparing Two Lists with VLOOKUP and ISNA 00:04:00 Lesson 11-Using the New XLookup Function-v2 00:07:00 Lesson 12-Using Dynamic Array functions-v2 00:06:00 Lesson 13-Other New Functions-v2 00:04:00 Section 04 Lesson 01-What are Text Functions 00:01:00 Lesson 02-Using CONCAT, CONCATENATE, AND TEXTJOIN 00:04:00 Lesson 03-Using Text to Columns 00:02:00 Lesson 04-Using LEFT, RIGHT, and MID Functions 00:03:00 Lesson 05-Using UPPER, LOWER, and PROPER Functions 00:02:00 Lesson 06-Using the Len Function 00:03:00 Lesson 07-Using the Trim Function 00:01:00 Lesson 08-Using the SUBSTITUTE Function 00:02:00 Section 05 Lesson 01-What are Date and Time Functions 00:02:00 Lesson 02-Using TODAY, NOW, and DAY Functions 00:03:00 Lesson 03-Using NETWORKDAYS and YEARFRAC Functions 00:03:00 Section 06 Lesson 01-Showing Formulas 00:03:00 Lesson 02-Tracing Precedents and Dependents 00:04:00 Lesson 03-Adding a Watch Window 00:04:00 Lesson 04-Error Checking 00:04:00 Section 07 Lesson 01-Using the Scenario Manager 00:07:00 Lesson 02-Using Goal Seek 00:03:00 Lesson 03-Analyzing with Data Tables 00:04:00 Section 08 Lesson 01-Understanding Protection 00:02:00 Lesson 02-Encrypting Files with Passwords 00:05:00 Lesson 03-Allowing Specific Worksheet Changes 00:02:00 Lesson 04-Adding Protection to Selected Cells 00:03:00 Lesson 05-Additional Protection Features 00:03:00 Section 09 Lesson 01-What are Macros 00:03:00 Lesson 02-Displaying the Developer Tab 00:03:00 Lesson 03-Creating a Basic Formatting Macro 00:05:00 Lesson 04-Assigning a Macro to a Button 00:03:00 Lesson 05-Creating Complex Macros 00:04:00 Lesson 06-Viewing and Editing the VBA Code 00:04:00 Lesson 07-Adding a Macro to the Quick Access Toolbar 00:03:00 Section 10 Lesson 01-What are Form Controls 00:02:00 Lesson 02-Adding a Spin Button and Check Boxes 00:04:00 Lesson 03-Adding a Combo Box 00:07:00 Section 11 Lesson 01-What is Data Validation 00:02:00 Lesson 02-Restricting Data Entry to the Whole Numbers 00:02:00 Lesson 03-Restricting Data Entry to a List 00:04:00 Lesson 04-Restricting Data Entry to a Date 00:02:00 Lesson 05-Restricting Data Entry to Specific Text Lengths 00:01:00 Lesson 06-Composing Input Messages 00:02:00 Lesson 07-Composing Error Alerts 00:03:00 Lesson 08-Finding Invalid Data 00:02:00 Lesson 09-Editing and Deleting Validation Rules 00:01:00 Section 12 Lesson 01-Working with Comments-v2 00:03:00 Lesson 02-Printing Comments and Errors 00:02:00 Lesson 03-Sharing a Workbook 00:04:00 Lesson 04-Co-Authoring in Excel 00:02:00 Lesson 05-Tracking Changes in a Workbook 00:03:00 Lesson 06-Working with Versions 00:03:00 Lesson 07-Sharing files Via Email-v2 00:03:00 Section 13 Lesson 01-Importing a Text File 00:04:00 Lesson 02-Exporting Data to a Text File 00:01:00 Course Recap Recap 00:02:00 Additional Materials Resource - Excel 365 Advanced 00:00:00 Final Exam Final Exam - Excel 365 Advanced 00:20:00

This course gets you started with the testing of web services and REST APIs using SoapUI features and tools. You will start with the basics and advance towards designing test frameworks for performing manual and automation testing on web services and APIs with the help of real-time projects.