1727 Analytics courses delivered Online

Unleash the power of data with our Data Analysis in Excel course, where you'll journey through the realm of spreadsheet analysis and uncover the secrets hidden within your data. In today's data-driven world, the ability to navigate, interpret, and extract insights from data is a coveted skill. Whether you're a professional looking to enhance your analytical capabilities or a student aiming to excel in data-driven fields, this course empowers you to harness Excel's full potential for data analysis. From modifying worksheets to forecasting future trends, you'll master the art of data manipulation, visualization, and analysis with confidence and precision. Learning Outcomes Master the art of modifying Excel worksheets to suit your data analysis needs. Discover advanced data analysis techniques, including working with lists and lookup functions. Create compelling data visualizations using charts, PivotTables, and PivotCharts. Effortlessly manage multiple worksheets and workbooks, making data organization a breeze. Apply data forecasting techniques and automate workbook functionality, saving time and boosting productivity. Why choose this Data Analysis in Excel 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 Data Analysis in Excel course for? Professionals seeking to enhance their data analysis skills. Students preparing for careers in data-driven industries. Analysts, researchers, and data enthusiasts eager to upskill. Business professionals looking to make data-driven decisions. Anyone interested in harnessing Excel for powerful data analysis. Career path Data Analyst: £25,000 - £47,000 Business Analyst: £26,000 - £50,000 Financial Analyst: £26,000 - £56,000 Market Research Analyst: £24,000 - £40,000 Operations Analyst: £23,000 - £48,000 Business Intelligence Analyst: £27,000 - £56,000 Prerequisites This Data Analysis in Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Analysis in Excel 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 Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Recommended Materials Workbook - Data Analysis in Excel 00:00:00 Assignment Assignment - Data Analysis in Excel 00:00:00

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There is a lot to learn in Power BI, this course takes a comprehensive look at the fundamentals of analysing data and includes a 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 utilise the online Power BI service. It looks at authoring tools that enable you to connect to and transform data from a variety of sources, allowing you to produce detailed reports through a range of visualisations, in an interactive and dynamic way. It also includes a detailed look at formulas by writing both M functions in Power Query, and DAX functions in Desktop view. This knowledge will allow you to take your reports to the next level. The aim of this course is to provide a complete introduction to understanding the Power BI analysis process, by working hands-on with examples that will equip you with the necessary skills to start applying your learning straight away. 1 Getting Started The Power BI ecosystem Opening Power BI Desktop Power BI's four views Introduction to Dashboards 2 Importing Files Importing data sources Importing an Excel file Importing a CSV file Importing a database Connect to an SQL Server Database Import vs. Direct Query Importing from the web Importing a folder of files Managing file connections 3 Shape Data in the Query Editor The process of shaping data Managing data types Keeping and removing rows Add a custom column Appending tables together Hiding queries in reports Fixing error issues Basic maths operations 4 The Data Model Table relationships Relationship properties 5 Merge Queries Table join kinds Merging tables 6 Inserting Dashboard Visuals Things to keep in mind Inserting maps Formatting Maps Inserting charts Formatting Charts Inserting a tree map Inserting a table, matrix, and card Controlling number formats About report themes Highlighting key points Filter reports with slicers Sync slicers across dashboards Custom web visuals 7 Publish and share Reports Publishing to Power BI service Editing online reports Pinning visuals to a dashboard What is Q&A? Sharing dashboards Exporting reports to PowerPoint Exporting reports as PDF files 8 The Power Query Editor Fill data up and down Split column by delimiter Add a conditional column More custom columns Merging columns 9 The M Functions Inserting text functions Insert an IF function Create a query group 10 Pivoting Tables Pivot a table Pivot and append tables Pivot but don't aggregate Unpivot tables Append mismatched headers 11 Data Modelling Expanded Understanding relationships Mark a date table 12 DAX New Columns New columns and measures New column calculations Insert a SWITCH function 13 Introduction to DAX Measures Common measure functions Insert a SUM function Insert a COUNTROWS function Insert a DISTINCTCOUNT function Insert a DIVIDE function DAX rules 14 The CALCULATE Measure The syntax of CALCULATE Insert a CALCULATE function Control field summarisation Things of note 15 The SUMX measure X iterator functions Anatomy of SUMX Insert a SUMX function When to use X functions 16 Time Intelligence Measures Importance of a calendar table Insert a TOTALYTD function Change financial year end date Comparing historical data Insert a DATEADD function 17 Hierarchies and Groups Mine data using hierarchies Compare data in groups

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

This course starts with data transformation strategies, exploring capabilities in the Power Query Editor, and data-cleansing practices. It looks at the Advanced Query Editor to view the M language code. This course focuses on advanced DAX measures that include filtering conditions, with a deep dive into time intelligence measures. Like the M query language, DAX is a rich functional language that supports variables and expression references. This course also looks at the creation of dynamic dashboards and incorporates a range of visualisations available in Power BI Desktop and online in the AppSource. The course finishes with a look at setting up end user level security in tables. 1 The query editor Split by row delimiter AddDays to determine deadlines Advanced query editor 2 Fuzzy matching joins Matching inconsistencies by percentage Matching with transformation table 3 Logical column functions Logical functions IF, AND, OR Using multiple conditions Including FIND in functions 4 Editing DAX measures Make DAX easier to read Add comments to a measure Using quick measures 5 The anatomy of CALCULATE Understanding CALCULATE context filters Adding context to CALCULATE with FILTER Using CALCULATE with a threshold 6 The ALL measure Anatomy of ALL Create an ALL measure Using ALL as a filter Use ALL for percentage 7 DAX iterators Anatomy of iterators A closer look at SUMX Using RELATED in SUMX Create a RANKX RANKX with ALL 8 Date and time functions Overview of functions Create a DATEDIFF function 9 Time intelligent measures Compare historical monthly data Create a DATEADD measure Creating cumulative totals Creating cumulative measures Visualising cumulative totals 10 Visualisations in-depth Utilising report themes Create a heatmap Comparing proportions View trends with sparklines Group numbers using bins Setting up a histogram 11 Comparing variables Visualising trendlines as KPI Forecasting with trendlines Creating a scatter plot Creating dynamic labels Customised visualisation tooltips Export reports to SharePoint 12 User level security Setting up row level security Testing user security

Overview This Microsoft Excel: Master Power Query course will unlock your full potential and will show you how to excel in a career in Microsoft Excel: Master Power Query. So upskill now and reach your full potential. Everything you need to get started in Microsoft Excel: Master Power Query is available in this course. Learning and progressing are the hallmarks of personal development. This Microsoft Excel: Master Power Query will quickly teach you the must-have skills needed to start in the relevant industry. In This Microsoft Excel: Master Power Query Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Microsoft Excel: Master Power Query skills to help you advance your career. Acquire a comprehensive understanding of various Microsoft Excel: Master Power Query topics and tips from industry experts. Learn in-demand Microsoft Excel: Master Power Query skills that are in high demand among UK employers, which will help you to kickstart your career. This Microsoft Excel: Master Power Query course covers everything you must know to stand against the tough competition in the Microsoft Excel: Master Power Query field.  The future is truly yours to seize with this Microsoft Excel: Master Power Query. Enrol today and complete the course to achieve a Microsoft Excel: Master Power Query certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Microsoft Excel: Master Power Query course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Microsoft Excel: Master Power Query course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Microsoft Excel: Master Power Query course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Microsoft Excel: Master Power Query is suitable for anyone aspiring to start a career in Microsoft Excel: Master Power Query; even if you are new to this and have no prior knowledge on Microsoft Excel: Master Power Query, this course is going to be very easy for you to understand.  And if you are already working in the Microsoft Excel: Master Power Query field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Microsoft Excel: Master Power Query course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Microsoft Excel: Master Power Query course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Microsoft Excel: Master Power Query course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Microsoft Excel: Master Power Query course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Microsoft Excel: Master Power Query Power Query Intro and Excel version 00:03:00 Excel Power Query - Introduction 00:03:00 Excel Power Query - Query Editor Ribbon 00:09:00 Transform Data - Trim in Excel Power Query 00:05:00 Transform Data - Format Dates and Values in Excel Power Query 00:02:00 Transform Data - Parsing URLs in Excel Power Query 00:05:00 Transform Data - Split Text Fields in Excel Power Query 00:10:00 Transform Data - Group By in Excel Power Query 00:03:00 Transform Data - Unpivoting Columns in Excel Power Query 00:05:00 Transform Data - Pivoting Columns in Excel Power Query 00:02:00 Transform Data - Split Columns into Other Columns in Excel Power Query 00:04:00 Transform Data - Filtering Rows in Excel Power Query 00:05:00 Transform Data - Sorting Columns in Excel Power Query 00:02:00 Transform Data - Transform and Add Columns in Excel Power Query 00:07:00 From Folder - Import From Folder in Excel Power Query 00:07:00 From Folder - Doing Auto Cleanup in Excel Power Query 00:13:00 From Folder - Extract Data from Forms in Excel Power Query 00:13:00 From Workbook - Extract Multiple Criteria in Excel Power Query 00:05:00 From Workbook - Extract Multiple Worksheets in Excel Power Query 00:04:00 Joins - Intro to Joins 00:04:00 Joins - Merging 00:08:00 Joins - Full Outer Join 00:06:00 Joins - Right Anti Join 00:09:00 Power Query - Convert Reports into Pivot Tables 00:05:00 Modulo 00:06:00

Ai (Artificial Intelligence) for Business Leaders Recognize the challenges and limitations of Generative AI, and gain insight into the future outlook of AI in business strategy. Equip yourself with the essential skills and knowledge needed to lead in an AI-driven business landscape. Learning Outcomes: Explain the fundamentals of Artificial Intelligence for business. Analyze the strategic impact of AI on business models. Evaluate the business implications of Generative AI. Assess the challenges and limitations of Generative AI. Predict the future role of AI in business strategy. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Ai (Artificial Intelligence) for Business Leaders Course Syllabus Ai (Artificial Intelligence) for Business: Gain a comprehensive understanding of AI and its significance in the business landscape, equipping you with the foundational knowledge to lead AI-driven initiatives. Strategic Impact of Ai (Artificial Intelligence) on Business: Explore how AI strategically impacts different business models, enabling you to identify opportunities for innovation and growth. Implications of Generative Ai (Artificial Intelligence): Delve into the applications and implications of Generative AI within business contexts, fostering the ability to harness its creative potential. Challenges of Ai (Artificial Intelligence): Understand the challenges and limitations associated with Generative AI, allowing you to make informed decisions and mitigate potential risks. Ai (Artificial Intelligence) in Business Strategy: Anticipate the future landscape of AI in business strategy, enabling you to proactively adapt and lead in an AI-driven environment. Leaders in Ai (Artificial Intelligence)-Driven Business: Develop the essential skills and knowledge required to lead AI-driven initiatives effectively, ensuring your leadership in the AI era is both informed and visionary.

Unlock the power of data analysis with our specialized Data Analysis in Excel Course. Learn essential techniques and tools to analyze data effectively using Microsoft Excel. Whether you're a beginner or looking to enhance your skills, this course provides hands-on training to help you interpret data, create insightful reports, and make informed business decisions. Enroll now to harness the full potential of Excel for data analysis and take your analytical skills to the next level.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for system and network administrators or operators responsible for the installation, setup, configuration, and administration of the BIG-IQ system or management of BIG-IP devices and F5 products running on those devices. This course uses lectures and hands-on exercises to give participants real-time experience in configuring and using the BIG-IQ© product. Students are introduced to BIG-IQ, its interface, and its various functionality. We first look at administering and operating the BIG-IQ system itself, then detail how it is used to remotely manage BIG-IP devices running BIG-IP Local Traffic Manager (LTM). We then look configuring a BIG-IQ Data Collection Device (DCD) system and see how it is used for the remote storage and examination of BIG-IP log events and statistics. Module 1: BIG-IQ Overview BIG-IQ Centralized Management BIG-IQ Components BIG-IQ Core Functionality REST API BIG-IQ Data Collection Device (DCD) BIG-IP Cloud Edition (CE) Setting up the BIG-IQ System Module 2: Administering the BIG-IQ System Controlling Access to the BIG-IQ Creating, Authenticating, Configuring Users Backups Local Host Settings Configuring DNS, NTP, and SMTP Monitoring BIG-IQ, DCD, and BIG-IP Events with Alerts Monitoring BIG-IQ with iHealth Post Installation Issues; Licensing, Changing Management IP, Master Key, Restoring Backups Module 3: Managing BIG-IP LTM Devices BIG-IP LTM Device Discovery BIG-IP Device Backup Deploying to BIG-IP Devices Deployment and Deployment Logs Configuration Snapshots Managing BIG-IP Certificates Managing BIG-IP Licenses Monitoring BIG-IP Devices with iHealth Management of QKView Reports from Managed BIG-IP Devices Module 4: Setting Up the BIG-IQ Data Collection Device Custom Roles Types and Groups Setting up User Accounts with custom roles and privileges Managing BIG-IP DSC Discovery and management of BIG-IP Device Clusters (DSC) with BIG-IQ Administering BIG-IQ High Availability Configuration and management of BIG-IQ systems in a High Availability pair

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice