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Course Overview This "Microsoft Power BI - Master Power BI in 90 Minutes!" course offers a concise yet comprehensive introduction to Power BI, empowering learners to quickly create and manage data dashboards. The course is designed for both newcomers and those looking to enhance their skills, covering essential topics to help users understand and utilise Power BI for data analysis and reporting. Upon completion, learners will gain the ability to design dynamic dashboards, manipulate data, and visualise trends, providing valuable insights for decision-making in various business environments. Course Description This course takes learners through Power BI’s core functionalities, starting with an introduction to the platform before advancing to building basic and sophisticated dashboards. Learners will explore key aspects such as data import, filtering, and the creation of interactive visuals. By working with live data, participants will develop an understanding of how to generate real-time reports, enhancing their ability to analyse data and derive insights. The course offers both beginner and advanced concepts, ensuring that all participants can apply what they’ve learned to real-world data scenarios. Upon completing the course, learners will feel confident in their ability to utilise Power BI to its full potential in any business context. Course Modules Module 01: Power BI - Introduction Module 02: Your First Power BI Dashboard Module 03: Your Advanced Power BI Dashboard with Real Live Data Module 04: Course Bonuses (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to improve data visualisation and reporting capabilities. Beginners with an interest in business intelligence or data management. Anyone looking to gain insights into data-driven decision-making. Career Path Business Intelligence Analyst Data Analyst Data Visualisation Specialist Marketing Data Analyst Financial Analyst

Dive deep into the vast realm of Python data science with our meticulously crafted course: 'Python Data Science with Numpy, Pandas and Matplotlib'. Explore the intricate details of Python, setting the stage with Pandas and Numpy, before delving into the power of Python data structures. With topics ranging from Python Strings to Matplotlib Histograms, you'll gain a holistic insight, ensuring that every dataset you touch unveils its story compellingly. So, if you're keen on transmuting raw data into visual masterpieces or insights, this journey is tailor-made for you. Learning Outcomes Grasp foundational knowledge of Python and its data structures like strings, lists, and dictionaries. Understand the potential of NumPy, from basic array operations to handling multi-dimensional arrays. Master the versatility of Pandas, encompassing everything from dataframe conversions to intricate operations like aggregation and binning. Efficiently manage, manipulate, and transform data using Pandas' diverse functionalities. Create visually striking and informative graphs using the power of Matplotlib. Why buy this Python Data Science with Numpy, Pandas and Matplotlib course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Python Data Science with Numpy, Pandas and Matplotlib there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Python Data Science with Numpy, Pandas and Matplotlib course for? Beginners eager to jumpstart their journey in Python data science. Analysts looking to enhance their data manipulation skills using Python. Statisticians keen on expanding their toolset with Python-based libraries. Data enthusiasts desiring a deep dive into Python's data libraries and structures. Professionals aiming to upgrade their data visualisation techniques. Prerequisites This Python Data Science with Numpy, Pandas and Matplotlib does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Data Science with Numpy, Pandas and Matplotlib was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Scientist: £40,000 - £80,000 Python Developer: £35,000 - £70,000 Data Analyst: £30,000 - £55,000 Business Intelligence Analyst: £32,000 - £60,000 Research Analyst: £28,000 - £52,000 Data Visualization Engineer: £33,000 - £65,000 Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:09:00 Introduction to Python, Pandas and Numpy Introduction to Python, Pandas and Numpy 00:07:00 System and Environment Setup System and Environment Setup 00:08:00 Python Strings Python Strings - Part 1 00:11:00 Python Strings - Part 2 00:09:00 Python Numbers and Operators Python Numbers and Operators - Part 1 00:06:00 Python Numbers and Operators - Part 2 00:07:00 Python Lists Python Lists - Part 1 00:05:00 Python Lists - Part 2 00:06:00 Python Lists - Part 3 00:05:00 Python Lists - Part 4 00:07:00 Python Lists - Part 5 00:07:00 Tuples in Python Tuples in Python 00:06:00 Sets in Python Sets in Python - Part 1 00:05:00 Sets in Python - Part 2 00:04:00 Python Dictionary Python Dictionary - Part 1 00:07:00 Python Dictionary - Part 2 00:07:00 NumPy Library - Introduction NumPy Library Intro - Part 1 00:05:00 NumPy Library Intro - Part 2 00:05:00 NumPy Library Intro - Part 3 00:06:00 NumPy Array Operations and Indexing NumPy Array Operations and Indexing - Part 1 00:04:00 NumPy Array Operations and Indexing - Part 2 00:06:00 NumPy Multi-Dimensional Arrays NumPy Multi-Dimensional Arrays - Part 1 00:07:00 NumPy Multi-Dimensional Arrays - Part 2 00:06:00 NumPy Multi-Dimensional Arrays - Part 3 00:05:00 Introduction to Pandas Series Introduction to Pandas Series 00:08:00 Introduction to Pandas Dataframes Introduction to Pandas Dataframes 00:07:00 Pandas Dataframe conversion and drop Pandas Dataframe conversion and drop - Part 1 00:06:00 Pandas Dataframe conversion and drop - Part 2 00:06:00 Pandas Dataframe conversion and drop - Part 3 00:07:00 Pandas Dataframe summary and selection Pandas Dataframe summary and selection - Part 1 00:06:00 Pandas Dataframe summary and selection - Part 2 00:06:00 Pandas Dataframe summary and selection - Part 3 00:07:00 Pandas Missing Data Management and Sorting Pandas Missing Data Management and Sorting - Part 1 00:07:00 Pandas Missing Data Management and Sorting - Part 2 00:07:00 Pandas Hierarchical-Multi Indexing Pandas Hierarchical-Multi Indexing 00:06:00 Pandas CSV File Read Write Pandas CSV File Read Write - Part 1 00:05:00 Pandas CSV File Read Write - Part 2 00:07:00 Pandas JSON File Read Write Pandas JSON File Read Write Operations 00:07:00 Pandas Concatenation Merging and Joining Pandas Concatenation Merging and Joining - Part 1 00:05:00 Pandas Concatenation Merging and Joining - Part 2 00:04:00 Pandas Concatenation Merging and Joining - Part 3 00:04:00 Pandas Stacking and Pivoting Pandas Stacking and Pivoting - Part 1 00:06:00 Pandas Stacking and Pivoting - Part 2 00:05:00 Pandas Duplicate Data Management Pandas Duplicate Data Management 00:07:00 Pandas Mapping Pandas Mapping 00:04:00 Pandas Grouping Pandas Groupby 00:06:00 Pandas Aggregation Pandas Aggregation 00:09:00 Pandas Binning or Bucketing Pandas Binning or Bucketing 00:08:00 Pandas Re-index and Rename Pandas Re-index and Rename - Part 1 00:04:00 Pandas Re-index and Rename - Part 2 00:05:00 Pandas Replace Values Pandas Replace Values 00:05:00 Pandas Dataframe Metrics Pandas Dataframe Metrics 00:07:00 Pandas Random Permutation Pandas Random Permutation 00:08:00 Pandas Excel sheet Import Pandas Excel sheet Import 00:07:00 Pandas Condition Selection and Lambda Function Pandas Condition Selection and Lambda Function - Part 1 00:05:00 Pandas Condition Selection and Lambda Function - Part 2 00:05:00 Pandas Ranks Min Max Pandas Ranks Min Max 00:06:00 Pandas Cross Tabulation Pandas Cross Tabulation 00:07:00 Matplotlib Graphs and plots Graphs and plots using Matplotlib - Part 1 00:06:00 Graphs and plots using Matplotlib - Part 2 00:02:00 Matplotlib Histograms Matplotlib Histograms 00:03:00 Resource File Resource File - Python Data Science with Numpy, Pandas and Matplotlib 00:00:00

Journalism is a noble and respective profession. Journalists bear the burden of presenting the crucial news and information to the mass people. If you want to build your career as a journalist or in the media industry, this journalism course can be the first step towards your professional journey. Learn the necessary skills you need to be a journalist from this Journalism course today. Our Journalism course lessons were prepared by experts and feature interactive activities. You'll learn how you can use various opportunities effectively from industry experts. This Journalism course has been divided into understandable and manageable sections that will help you grasp each concept- from the basic to advanced course components. Learn from industry experts today and enhance your skills and knowledge in no time. This Journalism course will increase your possibility to get your desired job and boost your personal growth. Learning Objectives Learn the basic principles of journalism Understand the roles and responsibilities of a journalist Familiarise with the ethical values and aspects of journalism Learn about various legal regulations and obligations Understand the language of journalism Be able to take notes fast and effectively Learn how to present your news attractively Grasp effective tips about data visualisation and presentation Who is this Course for? The Journalism course is ideal for highly aspiring individuals who wish to enhance their professional skills and train for the job they want! Also, this course is highly beneficial for people who want to have some in-depth knowledge on this topic and keep up to date with the latest information. So, you can enrol in this course if you are: Journalists Reporters Editors News Presenters News Researchers Study the Journalism course today and enhance your professional skillset from the comfort of your home! Entry Requirement There are no formal entry requirements for the Journalism course; with enrollment, this course is open to anyone! Anyone with a passion for learning about Journalism can enrol in this course without any hesitation. Although, the learner should be aged 16 or over to enrol in this course. Also, they need to have a good understanding of the English language to attend this course and understand what this course is about. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £4.99 and the hard copy for £9.99. Also, you can order both PDF and hardcopy certificates for £12.99. Career path This Journalism course will help you gain all the necessary theoretical knowledge to excel in the relevant field. Enrol on our Journalism course now and get started on the journey of taking your career to the next level. Course Curriculum Module 01: Introduction and Principles of Journalism Introduction and Principles of Journalism 00:18:00 Module 02: History and Development of Journalism History and Development of Newspaper Journalism 00:26:00 Module 03: Interviewing Interviewing 00:35:00 Module 04: Newspaper Journalism Newspaper Journalism 00:30:00 Module 05: News Writing, Production and Reporting News Writing, Production and Reporting 00:20:00 Module 06: Television Journalism Television Journalism 00:32:00 Module 07: Radio Journalism Radio Journalism 00:37:00 Module 08: Media Regulatory Bodies Media Regulatory Bodies 00:31:00 Module 09: Writing Skills for Journalists Writing Skills for Journalists 00:41:00 Module 10: Journalism law Journalism Law 00:35:00 Module 11: Defamation Defamation 00:20:00 Module 12: Journalism Ethics Journalism Ethics 00:17:00 Module 13: Health and Safety for Journalists Health and Safety for Journalists 00:38:00 Module 14: Niche Journalism Niche Journalism 00:24:00 Module 15: Tips on Writing a Good Feature Story Tips on Writing a Good Feature Story 00:34:00 Module 16: Online and Freelance Journalism Online and Freelance Journalism 00:16:00 Module 17: Becoming a Journalist Becoming a Journalist 00:29:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Introduction to Coding With HTML, CSS, & Javascript Course Overview "Introduction to Coding With HTML, CSS, & JavaScript" is a comprehensive course designed to equip learners with the foundational knowledge of web development. The course covers the essential programming languages – HTML, CSS, and JavaScript – focusing on creating interactive and responsive websites. Learners will gain proficiency in designing websites from scratch, using HTML for structure, CSS for styling, and JavaScript for adding dynamic features. By the end of the course, learners will have a well-rounded understanding of how to create websites that are functional, visually appealing, and user-friendly, preparing them for real-world web development tasks. Course Description This course takes learners through a structured journey in web development, starting with the basics and gradually advancing to more complex topics. The modules cover HTML from beginner to expert levels, CSS fundamentals to advanced styling techniques, and an in-depth exploration of JavaScript. The course includes practical projects that reinforce key concepts, such as building a website using HTML and CSS and incorporating JavaScript to enhance interactivity. Learners will also explore essential programming topics like functions, conditional statements, data visualisation, and client-side validation. By completing this course, learners will develop a solid foundation in web development, enabling them to create fully functional websites. Introduction to Coding With HTML, CSS, & Javascript Curriculum Module 01: Getting Started Module 02: Setting up Development Environment Module 03: HTML Fundamentals Module 04: HTML Intermediate Module 05: HTML Advanced Module 06: HTML Expert Module 07: HTML Website Project Module 08: CSS Fundamentals Module 09: CSS Intermediate Module 10: CSS Advanced Module 11: CSS Expert Module 12: CSS Website Project Module 13: JavaScript Getting Started Module 14: JavaScript Fundamentals Module 15: Strings Module 16: Operators Module 17: Conditional Statements Module 18: Control Flow Statements Module 19: Functions Module 20: Data Visualisation (Google Charts) Module 21: Error Handling Module 22: Client-side Validations Module 23: Publish Your Website for Live (See full curriculum) Who is this course for? Individuals seeking to build a career in web development. Professionals aiming to expand their technical skills in web programming. Beginners with an interest in learning web development. Anyone looking to design and develop their own websites. Career Path Front-end Developer Web Developer UI/UX Designer Web Development Specialist Digital Marketing Specialist Freelance Web Developer Web Designer

Learn to Code HTML, CSS, Javascript: Guide for Beginners Course Overview This course offers a comprehensive introduction to HTML, CSS, and JavaScript, designed for those looking to build a strong foundation in web development. Covering the essential web technologies, it equips learners with the skills to create fully functional websites and interactive web pages. From understanding basic structure and styling to mastering advanced JavaScript concepts, this course ensures that learners develop a solid understanding of how modern websites are built and maintained. By the end of the course, learners will be confident in their ability to build, style, and add functionality to websites, preparing them for a variety of web development roles. Course Description "Learn to Code HTML, CSS, and JavaScript: Guide for Beginners" takes learners through every stage of web development, starting with the core technologies: HTML, CSS, and JavaScript. It covers the fundamentals and gradually advances to more sophisticated techniques, helping learners build their skills step by step. The course explores HTML structure, CSS styling, and JavaScript logic, covering essential areas such as strings, operators, and control flow. In addition to these core concepts, learners will delve into client-side validations, error handling, and data visualisation. By the end of the course, students will be equipped to create professional websites and publish them for live use, with a full understanding of front-end development. Learn to Code HTML, CSS, Javascript: Guide for Beginners Curriculum Module 01: Getting Started Module 02: Setting up Development Environment Module 03: HTML Fundamentals Module 04: HTML Intermediate Module 05: HTML Advanced Module 06: HTML Expert Module 07: HTML Website Project Module 08: CSS Fundamentals Module 09: CSS Intermediate Module 10: CSS Advanced Module 11: CSS Expert Module 12: CSS Website Project Module 13: JavaScript Getting Started Module 14: JavaScript Fundamentals Module 15: Strings Module 16: Operators Module 17: Conditional Statements Module 18: Control Flow Statements Module 19: Functions Module 20: Data Visualisation (Google Charts) Module 21: Error Handling Module 22: Client-side Validations Module 23: Publish Your Website for Live (See full curriculum) Who is this course for? Individuals seeking to learn web development. Professionals aiming to enhance their web development skills. Beginners with an interest in building websites. Anyone looking to enter the tech industry or web development field. Career Path Front-End Developer Web Developer Web Designer UI/UX Developer JavaScript Developer Full-Stack Developer Website Project Manager Digital Marketer

SQL for Data Science, Data Analytics and Data Visualization Course Overview: This course offers a comprehensive introduction to SQL, designed for those looking to enhance their skills in data science, data analytics, and data visualisation. Learners will develop the ability to work with SQL databases, efficiently query and manage data, and apply these techniques for data analysis in both SQL Server and Azure Data Studio. By mastering SQL statements, aggregation, filtering, and advanced commands, learners will be equipped with the technical skills required to manage large datasets and extract meaningful insights. The course provides a solid foundation in data structures, user management, and working with multiple tables, culminating in the ability to perform complex data analysis and visualisation tasks. Course Description: This course covers a broad range of topics essential for anyone working with data in a professional capacity. From setting up SQL servers to mastering database management tools like SQL Server Management Studio (SSMS) and SQL Azure Data Studio, the course provides a thorough grounding in SQL. Learners will gain expertise in data structure statements, filtering data, and applying aggregate functions, as well as building complex SQL queries for data analysis. The course also includes instruction on SQL user management, group by statements, and JOINs for multi-table analysis. Key topics such as SQL constraints, views, stored procedures, and database backup and restore are also explored. The course incorporates SQL visualisation tools in Azure Data Studio, empowering learners to visualise data effectively. By the end of the course, learners will be proficient in SQL queries, data manipulation, and using Azure for data analysis. SQL for Data Science, Data Analytics and Data Visualization Curriculum: Module 01: Getting Started Module 02: SQL Server Setting Up Module 03: SQL Azure Data Studio Module 04: SQL Database Basic SSMS Module 05: SQL Statements for DATA Module 06: SQL Data Structure Statements Module 07: SQL User Management Module 08: SQL Statement Basic Module 09: Filtering Data Rows Module 10: Aggregate Functions Module 11: SQL Query Statements Module 12: SQL Group By Statement Module 13: JOINS for Multiple Table Data Analysis Module 14: SQL Constraints Module 15: Views Module 16: Advanced SQL Commands Module 17: SQL Stored Procedures Module 18: Azure Data Studio Visualisation Module 19: Azure Studio SQL for Data Analysis Module 20: Import & Export Data Module 21: Backup and Restore Database (See full curriculum) Who is this course for? Individuals seeking to enhance their data management and analysis skills. Professionals aiming to progress in data science, data analytics, or database administration. Beginners with an interest in data analysis and SQL databases. Anyone looking to gain expertise in SQL for Azure and SQL Server environments. Career Path: Data Analyst Data Scientist Database Administrator SQL Developer Business Intelligence Analyst Data Visualisation Specialist

Data Analysis: Data Analysis Training Have you ever wondered how companies get insights from massive volumes of data to stay competitive and make wise decisions? If so, then participate in our exclusive Data Analysis: Data Analysis Course. This Data Analysis Course describes the fundamentals of data, statistics, and an introduction to Data Analysis. How to get data and where to find it is explained in the Data Analysis Course. Moreover, this Data Analysis Course covers data cleansing, preprocessing, and exploratory data analysis (EDA). Additionally, the Data Analysis Course provides an introduction to Python and Excel for Data Analysis. This thorough Data Analysis Course includes lessons on data wrangling with Pandas (python) and data visualisation using Matplotlib and Seaborn (python). Enrol in our Data Analysis Course to study the fundamentals of statistical analysis and machine learning. Main Course: Data Analysis (Data Analytics) Training Free Courses included with Data Analysis: Data Analysis Training Course: Course 01: Minute Taking Course 02: GDPR Course 03: Cyber Security [ Note: Free PDF certificate as soon as completing the Data Analysis: Data Analysis Training Course] Data Analysis: Data Analysis Training Online This Data Analysis (Data Analytics) Training consists of 12 modules. Curriculum of Data Analysis (Data Analytics) Training Course Module 1: Introduction to Data Analytics Module 2: Basics of Data and Statistics Module 3: Data Collection and Sources Module 4: Data Cleaning and Preprocessing Module 5: Exploratory Data Analysis (EDA) Module 6: Introduction to Excel for Data Analytics Module 7: Introduction to Python for Data Analytics Module 8: Data Wrangling with Pandas (Python) Module 9: Data visualisation with Matplotlib and Seaborn (Python) Module 10: Introduction to Basic Statistical Analysis Module 11: Introduction to Machine Learning Module 12: Capstone Project - Exploratory Data Analysis Assessment Method of Data Analysis (Data Analytics) Training Course After completing Data Analysis: Data Analysis Training Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Data Analysis (Data Analytics) Training Course After completing the Data Analysis: Data Analysis Training Course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Data Analysis: Data Analysis Training Online For business professionals, entrepreneurs, or anybody else looking to have a thorough grasp of data analysis in a commercial setting, this Data Analysis Course is ideal. Requirements Data Analysis: Data Analysis Training Online To enrol in this Data Analysis: Data Analysis Training Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Data Analysis Training Course. Be energetic and self-motivated to complete our Data Analysis Training Course. Basic computer Skill is required to complete our Data Analysis Training Course. If you want to enrol in our Data Analysis Training Course, you must be at least 15 years old. Career path Data Analysis: Data Analysis Training Online This Data Analysis Course will assist you in obtaining positions as a business analyst, marketing analyst, data analysis, and in related fields.

Data Analysis: Data Analysis Course Would you like to acquire the skills and self-assurance necessary to make wise choices and successfully traverse the intricate and ever-changing realm of data analysis? Enrol in our Data Analysis Course. The fundamentals of data, statistics, and an introduction to data analysis are all covered in this data analysis course. The how-to of data collection and its sources are explained in the Data Analysis Course. This Data Analysis Course teaches preprocessing, data cleansing, and exploratory data analysis (EDA). An overview of Excel and Python for data analysis is explained in this Data Analysis Course. This extensive Data Analysis course includes lessons on data wrangling with Pandas (Python) and data visualisation using Matplotlib and Seaborn (Python). So, quickly join our Data Analysis Course to learn the fundamentals of machine learning and statistical analysis! Special Offers with free gifts for this Data Analysis: Data Analysis Course This Data Analysis Course course includes a FREE PDF Certificate. Lifetime access to this Data Analysis Course course Instant access to this Data Analysis Course course Get FREE Tutor Support to this Data Analysis Course Course Learning Outcome of Data Analysis Course This Data Analysis Course will help you learn about: Introduction to data analysis, basics of data, and statistics. Data Analysis Course explains how to collect data and its sources. Data cleaning, processing, and exploratory data analysis (EDA) are included in this Data Analysis Course. This Data Analysis Course describes an introduction to Excel for Data Analysis and Python for Data Analysis. Data Wrangling with Pandas (Python) and Data Visualisation with Matplotlib and Seaborn (Python) are parts of this comprehensive Data Analysis Course. With the help of this Data Analysis Course, you will learn the basics of statistical analysis and machine learning. Data Analysis: Data Analysis Course Embark on a transformative journey with our Data Analysis course, designed for beginners. Dive deep into the world of data analysis, mastering essential techniques and tools. Gain practical skills in Data Analysis, empowering you to unlock insights and drive informed decisions. Start your Data Analysis journey today! Who is this course for? Data Analysis: Data Analysis Course Anyone looking to have a thorough grasp of data analysis in a commercial setting should take this Data Analysis: Data Analysis Course. Requirements Data Analysis: Data Analysis Course To enrol in this Data Analysis: Data Analysis Course, students must fulfil the following requirements. To join in our Data Analysis: Data Analysis Course, you must have a strong command of the English language. To successfully complete our Data Analysis: Data Analysis Course, you must be vivacious and self driven. To complete our Data Analysis: Data Analysis Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Data Analysis: Data Analysis Course. Career path Data Analysis: Data Analysis Course With the assistance of this Data Analysis Course, you can obtain work as a data analyst, business analyst, marketing analyst, or in related fields.

Dive into the intricate world of numbers and data with our comprehensive 'Microsoft Excel & Accounting Training' course. Begin your journey by mastering the foundational elements of Microsoft Office Excel 2016, from the basics of worksheet modifications to the art of data visualisation using charts. As you progress, pivot your attention towards the meticulous realm of accounting. Here, you'll unravel the secrets of the accounting equation, immerse yourself in transaction analyses, and culminate your learning by understanding the complete accounting cycle. Whether you're looking to enhance your data management skills or embark on a career in accounting, this course is your stepping stone to success. Learning Outcomes: Acquire proficiency in utilising Microsoft Excel 2016 for data analysis, visualisation, and workbook management. Understand the core principles of accounting, including the accounting equation and transaction analysis. Demonstrate the ability to prepare financial statements and complete the accounting cycle. Implement advanced Excel features such as PivotTables, PivotCharts, and Lookup Functions. Apply knowledge in real-world scenarios, including fiscal year evaluations and spreadsheet exercises. Why buy this Microsoft Excel & Accounting Training? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Microsoft Excel & Accounting Training 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 Who is this Microsoft Excel & Accounting Training course for? Individuals aiming to bolster their data analysis and management capabilities. Aspiring accountants keen on understanding the fundamentals of the profession. Business owners desiring a deeper grasp of financial statements and accounting cycles. Students pursuing a career in finance or data management. Professionals looking to integrate Excel functionalities into their daily tasks. Career path Data Analyst: Average salary range: £25,000 - £40,000 Annually Accountant: Average salary range: £28,000 - £52,000 Annually Financial Controller: Average salary range: £40,000 - £70,000 Annually Management Accountant: Average salary range: £30,000 - £55,000 Annually Excel Specialist: Average salary range: £22,000 - £35,000 Annually Bookkeeper: Average salary range: £18,000 - £30,000 Annually Prerequisites This Microsoft Excel & Accounting Training does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Microsoft Excel & Accounting Training 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 **Microsoft Excel** Getting Started with Microsoft Office Excel 2016 Navigate the Excel User Interfact 00:28:00 Use Excel Commands 00:10:00 Create and Save a Basic Workbook 00:19:00 Enter Cell Data 00:12:00 Use Excel Help 00:05:00 Performing Calculations Create Worksheet Formulas 00:15:00 Insert Functions 00:17:00 Reuse Formulas and Functions 00:17:00 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 Formatting a Worksheet Apply Text Formats 00:16:00 Apply Number Format 00:07:00 Align Cell Contents 00:09:00 Apply Styles and Themes 00:12:00 Apply Basic Conditional Formatting 00:11:00 Create and Use Templates 00:08:00 Printing Workbooks Preview and Print a Workbook 00:10:00 Set Up the Page Layout 00:09:00 Configure Headers and Footers 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working with Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:23:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 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 Create and Modify Tables 00:16:00 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 00:12:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Sharing and Protecting Workbooks Collaborate on a Workbook 00:19:00 Protect Worksheets and Workbooks 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 **Accounting Training** Professional Bookkeeper Introduction Professional Bookkeeper 00:09:00 Introduction to Accounting and Business Defining a Business 00:07:00 Ethics in Accounting 00:05:00 Generally Accepted Accounting Principles (GAAP) 00:10:00 The Accounting Equation The Accounting Equation 00:07:00 Transactions 00:11:00 Financial Statements 00:13:00 Analyzing Transactions The Accounting Equation and Transactions 00:16:00 Double-Entry System 00:11:00 Transactions - Journalizing 00:17:00 Journal Entries 00:38:00 Entering Information - Posting Entries Posting Entries 00:10:00 The Trial Balance 00:10:00 Finding Errors Using Horizontal Analysis 00:09:00 Horizontal Trend : Balance Sheet 00:21:00 Horizontal Trend: Income Statement 00:36:00 Adjusting Process The Purpose of the Adjusting Process 00:15:00 Adjusting Entries Adjusting Entries - Prepaid Expenses 00:13:00 Adjusting Entries - Accrued Revenues 00:10:00 Adjusting Entries - Depreciation Expense 00:09:00 Adjustment Summary Adjustment Summary - Review 00:13:00 Vertical Analysis 00:33:00 Preparing a Worksheet Preparing a Worksheet 00:06:00 Financial Statements The Income Statement 00:11:00 Financial Statements - Definitions 00:12:00 Completing the Accounting Cycle Temporary vs. Permanent Account 00:19:00 The Accounting Cycle Illustrated Accounting Cycle Illustrated - Steps 1-5 00:11:00 Accounting Cycle Illustrated - Steps 6-10 00:12:00 Fiscal Year Fiscal Year 00:09:00 Spreadsheet Exercise Spreadsheet Exercise - Steps 1-4 00:11:00 Spreadsheet Exercise - Steps 5-7 00:37:00