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240 Pivot Table courses delivered Online

Microsoft Excel Crash Course 2024

5.0(1)

By LearnDrive UK

Master Excel in 2024 with our crash course! Learn essential tips, functions, and tools, including the exclusive XLOOKUP for Excel 2021 and Office 365, and unlock the full potential of data analysis.

Microsoft Excel Crash Course 2024
Delivered Online On Demand1 hour
£5

Mastering Microsoft Office 2021

5.0(1)

By LearnDrive UK

Master Microsoft Office 2021 with our comprehensive course. From Excel to PowerPoint and Word, learn essential tools and techniques for enhanced productivity and efficiency.

Mastering Microsoft Office 2021
Delivered Online On Demand1 hour
£5

Microsoft Excel

5.0(1)

By LearnDrive UK

This course will fully prepare you for virtually any Excel-related career path

Microsoft Excel
Delivered Online On Demand1 hour
£5

Microsoft Excel beginner to advanced

By IT's Easy Training

Full Excel Course Beginner to Advanced 6hrs

Microsoft Excel beginner to advanced
Delivered Online On Demand6 hours
£19.99

Excel Training: Advanced Tricks & Techniques

5.0(1)

By LearnDrive UK

A special focus will be put on advanced MS Excel tips and tricks for career advancement in this course.

Excel Training: Advanced Tricks & Techniques
Delivered Online On Demand1 hour
£5

0G53BG IBM SPSS Statistics Essentials (V26)

By Nexus Human

Duration 2 Days 12 CPD hours This course is intended for New users of IBM SPSS Statistics Users who want to refresh their knowledge about IBM SPSS Statistics Anyone who is considering purchasing IBM SPSS Statistics Overview Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables. Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders Additional course details: Nexus Humans 0G53BG IBM SPSS Statistics Essentials (V26) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 0G53BG IBM SPSS Statistics Essentials (V26) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

0G53BG IBM SPSS Statistics Essentials (V26)
Delivered OnlineFlexible Dates
Price on Enquiry

Oracle BI Publisher 12c R1: Fundamentals

By Nexus Human

Duration 3 Days 18 CPD hours This course is intended for Analyst Developer End User Implementer Overview Schedule and Burst Reports Perform Translations Create Reports Integrated With Oracle BI EE Administer BI Publisher Server Describe BI Publisher Technology and Architecture Create reports from OBI EE data sources Create and Modify Data Models Create RTF Templates by Using Template Builder Explore and Use the Form Field Method for Creating RTF Templates Create Layouts by Using the Layout Editor This Oracle BI Publisher 12c training will help you build a foundation of understanding how to best leverage this solution. Through Classroom Training or Live Virtual Class Training, you'll learn the ins and outs of how to use this solution. BI Publisher Technology and Architecture Functional Components Layout Templates Multitier Architecture Enterprise Server Architecture and Performance and Scalability Document Generation Process and Output Formats Supported Data Sources Bursting Overview Internationalization and Language Support Getting Started with BI Publisher Logging In, the Home Page, and Global Header, and Setting Account Preferences Viewing Reports Managing Repository Objects Managing Favorites Using Create Report wizard to Create Reports Selecting Data: Data Model, Spreadsheet, and BI Subject Area Configuring Report Properties Using the Data Model Editor Exploring the Schemas Used in the Course Exploring the Data Model Editor UI and the Supported Data Sources Creating a Private Data Source Creating a Simple Data Model based on a SQL Query Data Set Using Query Builder to Build a Query Viewing Data and Saving Sample Data Sets Adding Parameters and LOVs to the Query Configuring Parameter Settings and Viewing Reports with Parameters Working with Layout Editor Opening the Layout Editor and Navigating the Layout Editor UI Creating a Layout by Using a Basic Template Inserting a Layout Grid Adding a Table, Formatting Columns, Defining Sorts and Groups, and Applying Conditional Formats Inserting and Editing Charts, and Converting Charts to a Pivot Tables Adding Repeating Sections, Text Items, and Images Working with Lists, Gauges and Pivot Tables Creating Boilerplates Using Template Builder to Create RTF Templates Using the BI Publisher Menu Bar Creating an RTF Template from a Sample, Changing Field Properties, and Previewing Table Data Adding a Chart to an RTF Template Designing an RTF Template for a BI Publisher Report Creating a BI Publisher Report by Using Template Builder in Online Mode Exploring the Basic and Form Field Methods Exploring Advanced RTF Template Techniques Including Conditional Formats, Watermarks, Page-Level Calculations, Running Totals, Grouping, and Sorting BI Publisher Server: Administration and Security Describing the Administration Page Creating the JDBC Connections Setting, Viewing, and Updating Data Sources Describing the Security Model for BI Publisher and Oracle Fusion Middleware Describing Groups, Users, Roles, and Permissions Describing Delivery Options Including Print, Fax, Email, WebDav, HTTP Server, FTP, and CUPS Describing and Configuring BI Publisher Scheduler Integrating with Oracle BI Presentation Services and Oracle Endeca Server Scheduling and Bursting Reports Scheduling and Describing a Report Job and Related Options Managing and Viewing a Report Job Viewing Report Job History Scheduling a Report with Trigger Describing Bursting Adding a Bursting Definition to a Data Model Scheduling a Bursting Job Integrating BI Publisher with Oracle BI Enterprise Edition Configuring Presentation Services Integration Navigating Oracle BI EE Creating a Report based on OBI EE Subject Area Creating a Data Model and Report based on a BI Server SQL Query Creating a Data Model and Report based on an Oracle BI Analysis Adding a BI Publisher Report to an Oracle BI EE Dashboard Creating Data Models and BI Publisher Reports Based on Other Data Sources Configuring Presentation Services Integration Describing the Web Services Data Source Describing the HTTP (XML/RSS Feed) Data Source Explaining Proxy Setting for Web Services and HTTP Data Sources Creating a BI Publisher Report based on an External Web Service Creating a BI Publisher Report based on an HTTP Data Set Creating a BI Publisher Report Based on XML File Creating a BI Publisher Report Based on CSV Data source Performing Translations Describing Translation Types Translating by Using the Localized Template Option Translating by Using the XLIFF Option Managing XLIFF Translations on BI Publisher Server Describing the Overall Translation Process Describing Catalog Translation Exporting and Importing the XLIFF for a Catalog Folder Additional course details: Nexus Humans Oracle BI Publisher 12c R1: Fundamentals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Oracle BI Publisher 12c R1: Fundamentals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Oracle BI Publisher 12c R1: Fundamentals
Delivered OnlineFlexible Dates
Price on Enquiry

Excel - VBA Bootcamp

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for To ensure success, students should have completed Excel Essentials and Excel Functions Including Pivot Tables and Lookups or have the equivalent knowledge and experience. Overview Upon successful completion of this course, students will understand the programming environment of Visual Basic for applications and know how to create custom procedures and functions that can expand their ability to use Excel more effectively. This course is intended for the experienced Excel users that want to gain knowledge of visual basic for applications (VBA). Introduction to Macros Recording Macros Absolute and Relative How to Run a Macro Basics of Code Writing The VBA Environment (the ?VBE? window) Essential Tips, Tricks, Shortcuts Understanding VBA and Best Practice Crucial VBA Objects and Structures Variables and Data Types Conditionals (If, Select Case) Loops (For, Do) Interaction Interact with Data, Sheets, the Excel Application Interact with User (Message Box, Input Box) Errors Run Editing Debuging Handeling Errors Additional course details: Nexus Humans Excel - VBA Bootcamp training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Excel - VBA Bootcamp course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Excel - VBA Bootcamp
Delivered OnlineFlexible Dates
Price on Enquiry

Python With Data Science

By Nexus Human

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Python With Data Science
Delivered OnlineFlexible Dates
Price on Enquiry

Power BI - introduction to intermediate (2 days) (In-House)

By The In House Training Company

This course starts with the basics then moves seamlessly to an intermediate level. It includes a comprehensive yet balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to use the online Power BI service. It looks at authoring tools that enables you to connect to and transform data from a variety of sources, allowing you to produce dynamic reports using a library of visualisations. Once you have those reports, the course looks at the seamless process of sharing those with your colleagues by publishing to the online Power BI service. The aim of this course is to provide a strong understanding of the Power BI analysis process, by working with real-world examples that will equip you with the necessary skills to start applying your knowledge straight away. 1 Getting started The Power BI process Launching Power BI Desktop The four views of Power BI Dashboard visuals 2 Connecting to files Connect to data sources Connect to an Excel file Connect to a CSV file Connect to a database Import vs. DirectQuery Connect to a web source Create a data table 3 Transforming data The process of cleaning data Column data types Remove rows with filters Add a custom column Append data to a table Fix error issues Basic maths operations 4 Build a data model Table relationships Manage table relationships 5 Merge queries Table join kinds Merging tables 6 Create report visualisations Creating map visuals Formatting maps Creating chart visuals Formatting chart Tables, matrixes, and cards Control formatting with themes Filter reports with slicers Reports for mobile devices Custom online visuals Export report data to Excel 7 The power query editor Fill data up and down Split columns by delimiter Add conditional columns Merging columns 8 The M formula Creating M functions Create an IF function Create a query group 9 Pivot and unpivot tables Pivot tables in the query editor Pivot and append tables Pivot but don't summarise Unpivot tables Append mismatched headers 10 Data modelling revisited Data model relationships Mark a calendar as a date table 11 Introduction to calculated columns New columns vs. measures Creating a new column calculation The SWITCH function 12 Introduction to DAX measures Common measure categories The SUM measure Adding measures to visuals COUNTROWS and DISINCTCOUNT functions DAX rules 13 The CALCULATE measure The syntax of CALCULATE Things of note about CALCULATE 14 The SUMX measure The SUMX measure X iterator functions Anatomy of SUMX 15 Introduction to time intelligence Importance of a calendar table A special lookup table The TOTALYTD measure Change year end in TOTALYTD 16 Hierarchy, groups and formatting Create a hierarchy to drill data Compare data in groups Add conditional formatting 17 Share reports on the web Publish to the BI online service Get quick insights Upload reports from BI service Exporting report data What is Q&A? Sharing your reports 18 Apply your learning Post training recap lesson

Power BI - introduction to intermediate (2 days) (In-House)
Delivered in Harpenden or UK Wide or OnlineFlexible Dates
Price on Enquiry

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EduCBA

educba

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IIL Europe Ltd

iil europe ltd

London

At IIL, our fundamental values of Intelligence, Integrity, and Innovation guide our actions and achievements with each customer, partner, and colleague. Our deepest purpose is to foster the growth and success of individuals, teams, and organizations through enduring relationships and top-notch learning content delivered through various methods. Explore our learning categories: NEW Generative Artificial Intelligence Agile and Scrum Business Analysis Business Relationship Management Cybersecurity IT Management Lean Six Sigma Microsoft Project Project, Program and Portfolio Management INNOVATION IN PROFESSIONAL DEVELOPMENT & TRAINING IIL offers a wide variety of delivery methods to ensure an optimal learning experience. Using its proprietary Many Methods of Learning™, IIL delivers innovative, effective and consistent training solutions through a variety of learning approaches: * In-Person Classroom Courses * Self-Paced On-Demand Training * Live Virtual Classes * Simulations * Free Videos & Webinars * Mobile IIL ACCREDITING BODIES AND PARTNERSHIPS IIL is a PMI® Charter Global Registered Education Provider and member of PMI’s Global Executive Council as well as a Microsoft Partner (with a Microsoft Gold Project and Portfolio Management competency), IIL is also an Accredited Training Partner for: * PRINCE2 * ITIL * Association for Project Management (APM) * PeopleCert on behalf of AXELOS * IASSC Accredited Training Organization® * The American Council on Education (ACE), an APMG International Accredited Training Organization (ATO) * Scrum Alliance REA organization * Authorized CEU Sponsor Member of the International Association for Continuing Education and Training (IACET). * IIBA® Endorsed Education Provider. IIL is the training solution partner of choice for many top global companies.  * Women’s Business Enterprise National Council (WBENC) corporate member.