If you are looking forward to advance your skills with Microsoft Excel 2016 and want to learn more advanced skills or want to learn the topics covered in this course in the 2016 interface, this Excel 2016 Advanced will be the perfect choice for you! Through the course you will gain the skills necessary to use pivot tables, audit and analyze worksheet data, utilize data tools, collaborate with others, and create and manage macros. Additionally, you 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 your worksheets and workbooks. You will also learn about Excel's many collaboration features, as well as how to import and export data to and from your workbooks. What Will I Learn? Use Advanced IF Statements Use Advanced Lookup Functions Use Complex Logical and Text Functions Auditing Formulas Working with What-If Analysis Tools Protecting Worksheet and Workbook Use Advanced PivotTables and PowerPivot Tools Automate with Macros Work with Form Controls Ensure Data Integrity Collaborate in Excel Import and Export Data to a Text File Requirements Excel Introduction and Intermediate courses or equivalent experience. Who is the target audience? Students who want to expand their Excel knowledge. Introduction Introduction FREE 00:01:00 Using Advanced IF Statements Summarize Data with SUMIF FREE 00:04:00 Summarize Data with AVERAGIF 00:03:00 Summarize Data with COUNTIF 00:02:00 Using Advanced Lookup Functions Using VLOOKUP with TRUE to find an Approximate Match 00:04:00 Using HLOOKUP TRUE to find an Approximate Match 00:01:00 Using the Index Function 00:03:00 Using the Match Function 00:02:00 Creating a Combined Index and Match Formula 00:04:00 Comparing Two Lists with VLOOKUP 00:02:00 Comparing Two Lists with VLOOKUP and ISNA 00:04:00 Using Complex Logical and Text Functions Creating a Nested IF Function 00:03:00 Using the IFERROR Function 00:02:00 Using the LEN Function 00:02:00 Using the TRIM Function 00:01:00 Using the Substitute Function 00:02:00 Formula Auditing Showing Formulas 00:01:00 Tracing Cell Precedents and Dependents 00:03:00 Adding a watch Window 00:02:00 Error Checking 00:02:00 What-If Analysis Tools Using the Scenario Manager 00:03:00 Using Goal Seek 00:02:00 Analyzing with Data Tables 00:02:00 Worksheet and Workbook Protection Protection Overview 00:02:00 Excel File Password Encryption 00:03:00 Allowing Specific Worksheet Changes 00:01:00 Adding Protection to only Certain Cells in a Worksheet 00:03:00 Additional Protection Features 00:02:00 Advanced Use of PivotTables and PowerPivot Using the Pivot Tables Charts Wizard 00:02:00 Adding a Calculated Field 00:02:00 Adding a Caculated Item 00:02:00 Apply Conditional Formatting to a Pivot Table 00:03:00 Using Filters in the Pivot Table Fields Pane 00:02:00 Creating Filter Pages for a Pivot Table 00:01:00 Enabling a Power Pivot Add In 00:04:00 Automating with Macros What are Macros 00:03:00 Displaying the Developer Tab and Enabling Macros in Excel 00:03:00 Creating a Basic Formatting Macro 00:03:00 Running a Macro 00:02:00 Assigning a Macro to a Button 00:02:00 Creating a More Complex Macro 00:02:00 Viewing and Editing the VBA Code for an Existing Macro 00:03:00 Adding a Macro to the Quick Access Toolbar 00:02:00 Working with Form Controls What are Form Controls 00:02:00 Adding Spin Buttons and Check Boxes to a Spreadsheet 00:02:00 Adding a Combo Box to a Spreadsheet 00:02:00 Ensuring Data Integrity What is Data Validation 00:01:00 Restricting Data Entries to Whole Numbers 00:02:00 Data Validation Restricting Data Entry to a List 00:01:00 Data Validation Restricting Data Entry to a Date 00:01:00 Data Validation Restricting Data Entry to Different Text Lengths 00:01:00 Composing Input Messages 00:02:00 Composing Error Alters 00:02:00 Finding Invalid Data 00:02:00 Editing and Deleting Data Validation Rules 00:01:00 Collaborating in Excel Working with Comments 00:03:00 Printing Comments and Errors 00:02:00 Sharing a Workbook 00:03:00 Tracking Changes in a Workbook 00:03:00 Working with Versions 00:02:00 Sharing Files via Email 00:02:00 Importing and Exporting Data to a Text File Importing a Text File 00:03:00 Exporting a Text File 00:01:00 Conclusion Course Recap 00:01:00 Course Certification
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This comprehensive course, 'SQL for Data Science, Data Analytics, and Data Visualization,' covers essential SQL concepts and tools for working with data. Participants will learn to manipulate, analyze, and visualize data using SQL Server, Azure Data Studio, and other relevant tools. The course also delves into advanced SQL commands, stored procedures, and data import/export, making it ideal for aspiring data professionals. Learning Outcomes: Set up and configure SQL Server and SQL Azure Data Studio for data analysis. Master SQL statements for data manipulation, data structure, and user management. Utilize SQL queries, joins, and aggregate functions for efficient data analysis. Understand SQL constraints, views, and advanced commands for in-depth data exploration. Create and implement SQL stored procedures to automate tasks. Leverage Azure Data Studio for data visualization and perform data analysis with SQL. Why buy this SQL for Data Science, Data Analytics and Data Visualization? 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Course Curriculum Section 01: Getting Started Introduction 00:03:00 How to get course requirements 00:03:00 Getting started on Windows, Linux or Docker 00:01:00 How to ask great questions 00:01:00 FAQ's 00:01:00 Section 02: SQL Server setting up Section Introduction 00:02:00 Microsoft SQL Server Installation 00:19:00 SQL Server Management Studio (SSMS) Installation 00:08:00 How to connect MS SQL (Windows Authentication) 00:04:00 How to connect MS SQL (SQL Server Authentication) 00:03:00 Download and Restore Sample Database 00:07:00 Section 03: SQL Azure Data Studio What is Azure Data Studio 00:06:00 Azure Data Studio Installation steps 00:07:00 Azure Data Studio to Connect SQL Server 00:09:00 Create a Database 00:07:00 Create a Table 00:09:00 Insert Data rows 00:07:00 View the Data returned by Query 00:03:00 Section 04: SQL Database basic SSMS Section Introduction 00:01:00 Overview of Databases8 00:11:00 Creating Database 00:05:00 SQL Data Types 00:03:00 Column Data Types on SSMS 00:04:00 Creating Table 00:09:00 Overview of Primary Key and Foreign Key 00:04:00 Primary Key 00:04:00 Foreign Key 00:07:00 Creating Temporary tables 00:06:00 Section 05: SQL Statements for DATA Section Introduction 00:01:00 Insert statement 00:08:00 Update statement 00:05:00 Delete statement 00:03:00 Section 06: SQL Data Structure statements Section Introduction 00:01:00 CREATE table statement 00:03:00 DROP statement 00:02:00 ALTER statement 00:05:00 TRUNCATE statement 00:04:00 COMMENT in query 00:01:00 RENAME 00:02:00 Section 07: SQL User Management Create Database user 00:04:00 GRANT permissions 00:06:00 REVOKE permissions 00:04:00 Section 08: SQL Statement Basic Section Introduction 00:01:00 SQL Statement basic 00:03:00 SELECT Statement 00:07:00 SELECT DISTINCT 00:03:00 SELECT with column headings 00:03:00 Column AS statement 00:02:00 Section 09: Filtering Data rows SELECT WHERE Clause - theory 00:04:00 SELECT WHERE Clause - practical 00:07:00 Section 10: Aggregate functions Sum() 00:08:00 Min()-Max() 00:06:00 Section 11: SQL Query statements Order By statement 00:05:00 SELECT TOP clause in SQL 00:04:00 BETWEEN command 00:08:00 IN operator 00:04:00 Wildcard Characters and LIKE 00:05:00 Section 12: SQL Group by statement Section Introduction 00:01:00 Group by - theory8 00:03:00 Group by - practical 00:05:00 HAVING statement 00:04:00 Section 13: JOINS for Multiple table Data Analysis Overview of Joins 00:02:00 What are Joins 00:02:00 Inner join 00:08:00 Left outer join 00:03:00 Right outer join 00:02:00 Full outer join 00:01:00 Union 00:03:00 Cartesian Product with the Cross Join 00:03:00 Query Exercise 00:01:00 Solution for Query Exercise 00:01:00 Section 14: SQL Constraints Section introduction 00:01:00 Check constraint 00:07:00 NOT NULL constraint 00:08:00 UNIQUE constraint 00:05:00 Section 15: Views Creating Views 00:04:00 Reporting with multiple tables 00:03:00 Section 16: Advanced SQL commands Section Introduction 00:01:00 Timestamp 00:04:00 Extract from timestamp 00:03:00 Mathematical scalar functions 00:04:00 String functions 00:05:00 Sub Query 00:03:00 SELECT with calculations 00:06:00 Section 17: SQL Stored procedures Create stored procedure 00:05:00 Stored procedure with parameter 00:04:00 Section 18: Azure Data Studio Visualization Installing SandDance Extension 00:03:00 Visualization Charts 00:05:00 Multiple Table Data Charts 00:06:00 Section 19: Azure Studio SQL for Data Analysis Type Decision for Data Analysis 00:13:00 Data Analysis with Case Statement and String Text 00:09:00 Section 20: Import & Export data Section Introduction 00:01:00 Import Flat File 00:05:00 Import .csv or excel file 00:03:00 Export Data to Excel or any format 00:06:00 Section 21: Backup and Restore Database Section Introduction 00:01:00 Creating Database backup 00:04:00 Restoring Database backup 00:04:00
Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently
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This Transport and Logistics Advanced Diploma training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Transport and Logistics Advanced Diploma Requirements To participate in this Transport and Logistics Advanced Diploma course, all you need is - A smart device A secure internet connection And a keen interest in Transport and Logistics Advanced Diploma Career path You will be able to kickstart your Transport and Logistics Advanced Diploma career because this course includes various courses as a bonus. This Transport and Logistics Advanced Diploma is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Transport and Logistics Advanced Diploma career opportunities. Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free
***11 in 1 Exclusive Merchandising Package*** Give a compliment to your career and take it to the next level. This Merchandising will provide you with the essential knowledge and skills required to shine in your professional career. Whether you want to develop skills for your next job or want to elevate skills for your next promotion, this Merchandising course will help you keep ahead of the pack. The Merchandising incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can reinforce your professional skills and knowledge, reaching out to the level of expertise required for your position. Further, this Merchandising course will add extra value to your resume to stand out to potential employers. Along with this Merchandising course, you will get 10 other premium courses. Also, you will get an original Hardcopy and PDF certificate for the title course(Merchandising) and a student ID card absolutely free. What other courses are included with this Merchandising? Course 01: Merchandising Course 02: Visual Merchandising Course 03: Purchasing & Procurement Course - Level 3 Course 04: Social Media Marketing Training Course 05: Import/Export Processing Course 06: Level 3 Tax Accounting Course 07: Business Law Course 08: Business Analysis Level 3 Course 09: Branding Fundamentals for New Business Course 10: Warehouse Course 11: Business of Photography Key features of this Merchandising course: This Merchandising bundle is CPD QS Accredited Learn from anywhere in the world Entirely online Merchandising Training Lifetime access So, enrol Merchandising now to advance your career! Curriculum of Merchandising Bundle Course 1: Merchandising Module 01: Theory Module 02: Product Management Module 03: Merchandise Management Module 04: Inventory Management and Analysis Module 05: Strategy Module 06: Visual Merchandising Module 07: Merchandise Pricing Module 08: Importance of Consumer Behaviour Module 09: Consumer Rights Act Module 10: The Importance of Communicating with Customers How will I get my Merchandising Certificate? After successfully completing the Merchandisingcourse, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously, it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) Enrol Merchandising Bundle Today!! CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Merchandising bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this Merchandising course. Requirements Our Merchandising 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 Merchandising course, it can be studied in your own time at your own pace. Career path Having these Merchandising CPD certificate will increase the value in your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included