Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video 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 20 Hours 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 Availability | Certificate Providing Authority |
|---|---|
| yes | University of Illinois, Urbana ChampaignCoursera |
The Introduction to Accounting Data Analytics and Visualization Certification Fee will vary as per the number of months the learners want to stay on the course and explore the topic. The paid versions offer a shareable certificate, EMI options, refund option, and unlimited material access. The month-wise fee structure is provided in the table below:
Introduction to Accounting Data Analytics and Visualization Fee Structure
Duration | Amount (In INR) |
1 Month | INR 4,117 |
3 Months | INR 8,234 (INR 2,745 /month) |
6 Months | INR 12,352 ( INR 2,059 /month) |
What you will learn
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
- Learn on Your Terms
Readings
- Syllabus
- Glossary
- About the Discussion Forums
- ePub
- Learn More About Flexible Learning Paths
- Update Your Profile
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
Reading
Module 1 Overview and Resources
Practice Exercises
- Lesson 1.1 Knowledge Check
- Lesson 1.2 Knowledge Check
- Introduction to Accountancy Analytics: Quiz
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
Reading
- Module 2 Overview and Resources
Practice Exercises
- 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 and Resources
Practice Exercises
- 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
Reading
Module 4 Overview and Resources
Practice Exercises
- 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 and Resources
Practice Exercises
- 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
Practice Exercises
- Lesson 6.1 Knowledge Check
- Lesson 6.2 Knowledge Check
- Lesson 6.4 Knowledge Check
- Analytic Tools in Excel 1: Quiz
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
Practice Exercises
- 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 and Resources
- Congratulations!
- Get Your Course Certificate
Practice Exercises
- Lesson 8.1 Knowledge Check
- Lesson 8.2 Knowledge Check
- Lesson 8.3 Knowledge Check
- Automation in Excel: Quiz
Instructors
University of Illinois, Urbana Champaign Frequently Asked Questions (FAQ's)
The online programme is the first course in the four Accounting Data Analytics Specialization courses.
The online course is taught by Ronald Guymon who is the Senior Lecturer of Accountancy at the University of Illinois at Urbana-Champaign.
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.
The learners can complete the online programme within about 20 hours.
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.