Course Overview Grasp the opportunity to learn Microsoft Excel from the ABCs to an advanced level within one course. The Microsoft Excel Masterclass in 2021 course will start with the basics with MS excel and gradually turn you into an expert user. The Microsoft Excel Masterclass in 2021 course will first focus on the tools and functions of excel. You will comprehend the skills to create basic formulas in excel. In this step by the step learning process, you will have the adequate knowledge and ability to make all sorts of adjustments to your worksheets. The course will teach you many strategies for cell formatting. From the easy to follow modules, you will grasp the techniques to insert shapes and images into your sheets. You will also understand how to visualize your data in charts. In the end, you will study the benefits of using excel templates. The Microsoft Excel Masterclass in 2021 course will provide you with first-hand training on excel. Enroll in the course and take your excel skills to the next level. Learning Outcomes Get an introduction to Microsoft Excel and its functions Understand the process of data validation and data visualization Learn how to adjust excel worksheets Know about the conditional functions Familiarize yourself with the process of inserting images and shapes Who is this course for? Those who want to learn Microsoft Excel. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The Microsoft Excel Masterclass in 2021 course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Business Professional Data Operator Administrative Officer Data Analyst Unit 01: Excel from A-Z Course Introduction Excel from A-Z Course Intro 00:03:00 Excel Job Opportunities 00:03:00 Excel Job Types 00:04:00 Microsoft Excel Marketplace 00:04:00 What is Microsoft Excel? 00:04:00 Who is This Course For? 00:04:00 Unit 02: Getting Started With Excel Finding & Opening Excel 00:01:00 Excel's Start Screen 00:03:00 Explaining the Excel Interface 00:03:00 Excel Interface Continued 00:01:00 Excel Workbook vs. Excel Worksheet 00:02:00 Saving an Excel Document 00:04:00 Customizing the Quick Access Toolbar 00:02:00 Customizing the Excel Ribbon 00:03:00 Excel Shortcut Keys 00:02:00 Unit 03: Values, Referencing and Formulas Creating Excel Labels 00:03:00 Entering Numeric Values in Excel 00:03:00 Formatting Date Values in Excel 00:05:00 Building Basic Formulas in Excel 00:05:00 Order of Operations 00:06:00 Relative vs. Absolute Cell References 00:07:00 Unit 04: Intro to Excel Functions Excel Functions Explained 00:03:00 The SUM() Function 00:08:00 The MIN() & MAX() Function 00:04:00 The AVERAGE() Function 00:02:00 COUNT() Functions 00:05:00 Unit 05: Adjusting Excel Worksheets Moving & Copying Data 00:07:00 Insert & Delete Rows and Columns 00:05:00 Adjusting the Width and Height of Cells 00:05:00 Hiding and Unhiding Excel Rows and Columns 00:04:00 Renaming, Moving & Deleting Excel Worksheets 00:05:00 Adding Protection to Specific Cells 00:04:00 Protecting the Structure of a Workbook 00:02:00 Adding a Workbook Password to Open File 00:02:00 Unit 06: Visually Pleasing Cell Formatting Formatting Fonts and Cell Background Color 00:05:00 Adding Cell Borders 00:05:00 Formatting Data Appropriately 00:05:00 The Magic behind Excel's Format Painter 00:04:00 Creating Styles for Formatting Efficiency 00:06:00 Merging Cells for a Cleaner Look 00:03:00 The Power of Conditional Formatting 00:06:00 Unit 07: How to Insert Images and Shapes! Grab User's Attention using Illustrations 00:09:00 Customizing Icons 00:05:00 Create Compelling Graphics with SmartArt 00:06:00 Unit 08: Visualize Data with Charts The Commonly Used Column Chart 00:03:00 Changing the Chart Design 00:02:00 Formatting Elements of a Chart 00:06:00 Modifying the Data, Type & Location of a Chart 00:06:00 Unit 09: Excel's Printing Options Print Preview Options 00:04:00 Excel's Page Layout View 00:07:00 Printing a Specific Range of Cells 00:03:00 Converting Spreadsheets to PDF Files 00:02:00 Unit 10: Benefits of Using Excel Templates Why Create an Excel Template 00:01:00 How to Create an Excel Template 00:05:00 Unit 11: Working with Excel Datasets How to Prepare Data for Analysis 00:04:00 How to Sort Data in Excel 00:03:00 Multi-Level Sorting 00:03:00 Custom Sorting Datasets in Excel 00:02:00 Applying Filters to Datasets 00:05:00 Creating Subtotals within a Dataset 00:06:00 Converting Datasets into Tables 00:06:00 Finding & Removing Duplicate Values 00:07:00 Unit 12: Excel Database Functions The SUMIF() Function 00:09:00 The DSUM() Function 00:08:00 The DSUM() Function Cont. 00:07:00 The SUBTOTAL() Function 00:06:00 Unit 13: Excel Data Validation What is Excel Data Validation? 00:02:00 Creating a Drop Down List with Data Validation 00:07:00 Different Types of Excel Data Validation 00:06:00 Adding Custom Alerts to Data Validation 00:07:00 Creating a Dynamic Drop Down List 00:03:00 Complex Validation: Dependent Drop Down List! 00:09:00 Unit 14: Excel PivotTables Creating an Excel Pivot Table 00:06:00 Modifying Excel PivotTables 00:06:00 Grouping & Filtering PivotTable Data 00:07:00 Drilling Down into PivotTable Data 00:02:00 Creating Pivot Charts & Utilizing Slicers 00:08:00 Unit 15: Excel's PowerPivot Add-In What is PowerPivot? 00:04:00 Activating the Excel PowerPivot Add-In 00:02:00 Creating Relationships between Data Tables 00:06:00 Using Data Models to Create PivotTables 00:05:00 How to Create PowerPivot KPI's 00:08:00 Unit 16: Excel's Conditional Functions Excel's IF() Function 00:05:00 IF() Function with AND() Criteria 00:05:00 IF() Function with OR() Criteria 00:05:00 Nesting Multiple IF() Functions 00:07:00 The COUNTIF() Function 00:04:00 Key Benefits of Named Ranges 00:04:00 Unit 17: Excel's Lookup Function VLOOKUP() Function 00:09:00 The Beauty of Excel's IFERROR() Function 00:04:00 HLOOKUP() Function 00:06:00 INDEX() Function 00:05:00 MATCH() Function 00:05:00 INDEX() and MATCH() Combined 00:05:00 Two-Way Lookup with INDEX() and MATCH() 00:04:00 Unit 18: Text Based Functions in Excel LEFT(), RIGHT() and MID() Function 00:07:00 Extracting Specific Text using LEN() & SEARCH() 00:13:00 Combining Text with CONCATENATE() 00:06:00 Quick Tips & Other Text Based Functions 00:06:00 Unit 19: Auditing Formulas and Views in Excel Tracing Precedents & Dependents in Formulas 00:04:00 Showing Formulas 00:02:00 Grouping Data 00:03:00 3D Referencing in Formulas 00:05:00 Utilizing the Watch Window in Excel 00:03:00 How to Freeze Panes in Excel 00:03:00 Unit 20: Excel's 'what If?' Tools Excel's Scenario Manager Tool 00:06:00 Goal Seek in Excel 00:06:00 Compare Results with Excel Data Tables 00:04:00 Solver Tool 00:11:00 Unit 21: Welcome to Excel VBA The Power Behind Excel VBA 00:03:00 A Look Inside the Visual Basic Editor (VBE) 00:04:00 Recording a Macro 00:09:00 Saving & Opening a Macro-Enabled Workbook 00:02:00 Unit 22: The VBA Language Modules and Procedures 00:07:00 Objects, Methods and Properties 00:06:00 Excel VBA Variables 00:05:00 Unit 23: Writing VBA Code Referencing a Range 00:14:00 InputBox & MsgBox 00:06:00 Using Variables in VBA Code 00:05:00 If Then Else Statement 00:10:00 Worksheet Functions inside VBA 00:08:00 Creating User Defined Functions 00:09:00 User Defined Functions within VBA Scripts 00:06:00 Unit 24: Important VBA Tools and Logic Find Last Row of Data 00:06:00 Find Last Column of Data 00:03:00 With Statement 00:05:00 Debugging & Error Handling 00:07:00 Debugging & Error Handling Cont. 00:07:00 Unit 25: Excel VBA Lopps For Next Loop 00:09:00 Do Until Loop 00:06:00 For Each Loop 00:04:00 Unit 26: Triggering Macros Assigning Macros to Shapes 00:04:00 Form Controls vs ActiveX Controls 00:08:00 Worksheet Events 00:04:00 Workbook Events 00:03:00 Fun with VBA Events! 00:07:00 Unit 27: Excel User Forms Creating an Excel UserForm 00:03:00 Adding Controls to UserForms 00:10:00 How to Show an UserForm 00:03:00 Passing TextBox Values to Desired Cells 00:07:00 Passing Option Buttons to Desired Cells 00:07:00 UserForm ComboBoxes 00:08:00 Clearing Values from UserForm Controls 00:03:00 How to Close an UserForm 00:02:00 UserForms and Protected Sheets 00:05:00 Unit 28: Starting a Career in Excel Creating an Excel Resume 00:05:00 Getting Started with Freelancing 00:06:00 How to Become an Excel Freelancer 00:05:00 Top Freelance Websites 00:05:00 How to Get Your First Client 00:08:00 Personal Branding 00:07:00 Networking Do's and Don'ts 00:04:00 Importance of Having a Website 00:04:00 Resources Resources - Microsoft Excel Masterclass in 2021 00:00:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
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Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00
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In this course, we will master the syntax and structure of RSpec then learn to utilize test-driven development principles to design and implement clean test specs and reduce dependencies in the test suite by mocking objects with class and instance doubles. We will also explore the wide collection of RSpec matches available to test the code.
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