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    Quick Facts

    Medium Of InstructionsMode Of LearningMode Of Delivery
    EnglishSelf StudyVideo and Text Based

    Course Overview

    Introduction to Accounting Data Analytics and Visualization is an online course designed for beginner-level students. The online programme is meant to help the accounting students to have analytical skills and equip them with the capacity to manage the data analytic programming languages such as R, Python and whatnot. Introduction to Accounting Data Analytics and Visualization Certification Syllabus will explore various aspects of financial accounting and analytics including data assembling, the process of big data analysis using Excel and Tableau and many more. 

    Introduction to Accounting Data Analytics and Visualization Certification Course, the online programme by Coursera, is offered by the University of Illinois at Urbana-Champaign. It is the first course in the four Accounting Data Analytics Specialization courses. After the completion of the Introduction to Accounting Data Analytics and Visualization Certification by Coursera, the learners will be provided with a certificate of completion after making the payment of the fee prescribed by Coursera. 

    The Highlights

    • Provided by Coursera
    • Offered by the University of Illinois at Urbana-Champaign
    • Self-Paced Learning Option
    • 100% Online Course
    • Around 2 weeks to Complete 
    • Flexible Deadlines
    • Shareable Certificate
    • Financial Aid Available

    Programme Offerings

    • English videos with multiple subtitles
    • BeginnerLevel course
    • Shareable Certificate
    • Financial aid available.

    Courses and Certificate Fees

    Certificate AvailabilityCertificate Providing Authority
    yesUniversity of Illinois, Urbana ChampaignCoursera

    Introduction to Accounting Data Analytics and Visualization Fee Structure

    Duration

    Amount (In INR)

    1 Month 

    INR 1,699

    3 Months 

    INR 3,499

    6 Months 

    INR 5,199


    What you will learn

    Accounting proficiencyData science knowledge

    By the end of the  Introduction to Accounting Data Analytics and Visualization Training, the learners will be able to learn the following concepts:

    • Data Analysis
    • Predictive Analytics
    • Data Visualization (DataViz)
    • Data Architecture
    • Coding

    Who it is for

    Introduction to Accounting Data Analytics and Visualization Classes is highly recommended for professionals including Accountant, Account Manager, Big Data Analytics Engineer, Big data engineer, Data Engineer and the like.


    Admission Details

    Step 1 - At first, the candidates need to register and sign up at https://www.coursera.org/ 

    Step 2 - Search for ‘The University of Illinois at Urbana-Champaign’ and the online courses offered by the university will appear. 

    Step 4 - Search for ‘Introduction to Accounting Data Analytics and Visualization’. 

    Step 5- Click the option  ‘enrol’ and start pursuing the online programme. 

    The Syllabus

    Videos
    • Course Introduction
    • About Ronald Guymon
    Readings
    • Syllabus
    • Glossary
    • About the Discussion Forums
    • ePub
    • Learn More About Flexible Learning Paths
    • Update Your Profile
    Discussion Prompt
    • Get to Know Your Fellow Learners
    Plugin
    • Welcome! Please Tell Us About Yourself.

    Videos
    • Module 1 Introduction
    • 1.1.1 History and Future of Accounting
    • 1.1.2 The Importance of Data and Analytics in Accounting
    • 1.1.3 Humans' Relationship with Data
    • 1.1.4 Accountants' Role in Shaping How Data Is Used
    • 1.1.5 Data Analytics Tools: Spreadsheets vs. Data Science Languages
    • 1.2.1 Advanced Data Analytics in Managerial Accounting Overview
    • 1.2.2 Advanced Data Analytics in Auditing Overview
    • 1.2.3 Advanced Data Analytics in Financial Accounting Overview
    • 1.2.4 Advanced Data Analytics in Taxes Overview
    • 1.2.5 Advanced Data Analytics in Systems Accounting Overview
    • Module 1 Conclusion
    Readings
    • Module 1 Overview
    • Module 1 Readings
    Quizzes
    • Lesson 1.1 Knowledge Check
    • Lesson 1.2 Knowledge Check
    • Introduction to Accountancy Analytics: Quiz
    Discussion Prompt
    • Make Connections to Topic

    Videos
    • Module 2 Introduction
    • 2.1.1 Making Room for Empirical Enquiry
    • 2.1.2 System 1 vs. System 2 Mindset
    • 2.2.1 Linking Core Courses to Analytical Thinking
    • 2.2.2 Inductive and Deductive Reasoning
    • 2.2.3 Advanced Analytics and the Art of Persuasion
    • 2.3.1 FACT Framework: Frame the Question
    • 2.3.2 FACT Framework: Assemble the Data
    • 2.3.3 FACT Framework: Calculate Results
    • 2.3.4 FACT Framework: Tell Others About the Results
    • 2.3.5 FACT Framework Review
    • Module 2 Conclusion
    Readings
    • Module 2 Overview
    • Module 2 Readings
    Quizzes
    • Lesson 2.1 Knowledge Check
    • Lesson 2.2 Knowledge Check
    • Lesson 2.3 Knowledge Check
    • Accounting Analysis and an Analytics Mindset: Quiz

    Videos
    • Module 3 Introduction: What is Data?
    • 3.1.1 Characteristics that Make Data Useful for Decision Making
    • 3.2.1 Structured vs. Unstructured Data
    • 3.2.2 Properties of a Tidy Dataframe
    • 3.2.3 Data Types
    • 3.2.4 Data Dictionaries
    • 3.3.1 Wide Data vs. Long Data
    • 3.3.2 Merging Data
    • 3.3.3 Data Automation
    • 3.4.1 Visualization Distributions
    • 3.4.2 Visualizing Data Relationships
    • Module 3 Conclusion
    Reading
    • Module 3 Overview
    • Module 3 Readings
    Quizzes
    • Lesson 3.2 Knowledge Check
    • Lesson 3.4 Knowledge Check
    • Data and Its Properties: Quiz

    Videos
    • Module 4 Introduction
    • 4.1.1 Why Visualize Data?
    • 4.1.2 Visual Perception Principles
    • 4.1.3 Data Visualization Building Blocks
    • 4.2.1 Basic Chart Data
    • 4.2.2 Scatter Plots
    • 4.2.3 Bar Charts
    • 4.2.4 Box and Whisker Plots
    • 4.2.5 Line Charts
    • 4.2.6 Maps
    • 4.3.1 Financial Chart Data
    • 4.3.2 Waterfall Charts
    • 4.3.3 Candlestick Charts
    • 4.3.4 Treemaps and Sunburst Charts
    • 4.3.5 Sparklines and Facets
    • 4.3.6 Charts to Use Sparingly
    • Module 4 Conclusion
    Readings
    • Module 4 Overview
    • Module 4 Readings
    Quizzes
    • Lesson 4.1 Knowledge Check
    • Lesson 4.2 Knowledge Check
    • Lesson 4.3 Knowledge Check
    • Data Visualization 1: Quiz

    Videos
    • Module 5 Introduction
    • 5.1.1 Getting Started with Tableau
    • 5.1.2 Scatter Plots in Tableau 
    • 5.1.3 Scatter Plots in Tableau 
    • 5.1.4 Bar Charts and Histograms in Tableau
    • 5.1.5 Box Plots and Line Charts in Tableau
    • 5.2.1 Adding Dimensions in Tableau
    • 5.2.2 Facets and Groups in Tableau
    • 5.3.1 Data Joins in Tableau
    • 5.3.2 Tableau Analytics - Forecasts
    • 5.3.3 Tableau Analytics - Clusters and Confidence Intervals
    • 5.4.1 Communicating Tableau Analyses
    • Module 5 Conclusion
    Reading
    • Module 5 Overview
    • Module 5 Readings
    Quizzes
    • Lesson 5.2 Knowledge Check
    • Lesson 5.4 Knowledge Check
    • Data Visualization 2: Quiz

    Videos
    • Module 6 Introduction
    • 6.1.1 Framing a Question: Larry's Commissary
    • 6.1.2 Assembling Data
    • 6.1.3 Data Analysis ToolPak and Descriptive Statistics
    • 6.1.4 Correlation
    • 6.2.1 Linear Models
    • 6.2.2 Simple Regression
    • 6.2.3 Regression Diagnostics 1: Regression Summary, ANOVA, and Coefficient Estimates
    • 6.3.1 Multiple Regression
    • 6.3.2 Regression Diagnostics 2: Predicted Values, Residuals, and Standardized Residuals
    • 6.3.3 Regression Diagnostics 3: Line Fit Plots, Adjusted R Square, and Heat Maps for P-Values
    • 6.4.1 Making a Forecast with a Linear Model
    • Module 6 Conclusion
    Reading
    • Module 6 Overview and Resources

    Quizzes
    • Lesson 6.1 Knowledge Check
    • Lesson 6.2 Knowledge Check
    • Lesson 6.4 Knowledge Check
    • Analytic Tools in Excel 1: Quiz
    Peer Review
    • Analytic Tools in Excel 1: Peer Review Assignment

    Videos
    • Module 7 Introduction
    • 7.1.1 Polynomial Regression Models
    • 7.1.2 Categorical Variables
    • 7.1.3 Multiple Indicator Variables
    • 7.1.4 Interaction Terms
    • 7.1.5 Regression Summary
    • 7.2.1 Optimization with Excel Solver
    • 7.2.2 Solver Constraints and Reports
    • 7.3.1 Logit Transformation
    • 7.3.2 Simple Logistic Regression
    • 7.3.3 Logistic Regression Accuracy
    • Module 7 Conclusion
    Reading
    • Module 7 Overview and Resources

    Quizzes
    • Lesson 7.1 Knowledge Check
    • Lesson 7.3 Knowledge Check
    • Analytic Tools in Excel 2: Quiz

    Videos
    • Module 8 Introduction
    • 8.1.1 Recording Macros
    • 8.1.2 Basics of VB Editor
    • 8.1.3 Basics of VBA
    • 8.2.1 For Loops, Variables, Index Numbers, and Last Rows
    • 8.2.2 Programming Hints
    • 8.2.3 Conditional Statements
    • 8.3.1 Macro for Creating Multiple Histograms
    • 8.3.2 Clustering Overview
    • 8.3.3 K-Means Clustering in Excel
    • 8.3.4 K-Means Clustering Macro
    • 8.3.5 Clustering On a Larger Scale
    • Module 8 Conclusion
    • Gies Online Programs
    Readings
    • Module 8 Overview
    • Congratulations on completing the course!
    • Get Your Course Certificate
    • Module 8 Readings
    Quizzes
    • Lesson 8.1 Knowledge Check
    • Lesson 8.2 Knowledge Check
    • Lesson 8.3 Knowledge Check
    • Automation in Excel: Quiz
    Plugin
    • How Was the Course?

    Instructors

    University of Illinois, Urbana Champaign Frequently Asked Questions (FAQ's)

    1: To which specialization the Introduction to Accounting Data Analytics and Visualization online course belong?

    The online programme is the first course in the four Accounting Data Analytics Specialization courses.

    2: Who teaches the Accounting Data Analytics Specialization online programme?

    The online course is taught by Ronald Guymon who is the  Senior Lecturer of Accountancy at the University of Illinois at Urbana-Champaign.

    3: Can learners who are not familiar with English join the online programme?

    Yes, learners around the globe can join the online course regardless of their linguistic background because the subtitles are available in all major international languages like Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, and Spanish.

    4: How many hours will it take to complete the online certificate programme?

    The learners can complete the online programme within about 2 weeks. 

    5: What is the fee structure of the programmes? What if someone struggles to make the fee payment?

    The fee will depend completely on how many months the students will continue on the course. The students who cannot afford the fee can apply for the scholarship provided by Coursera.

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