Accounting has always been about analytical thinking. From the earliest days of the profession, Luca Pacioli emphasized the importance of math and order for analyzing business transactions. The skillset that accountants have needed to perform math and to keep order has evolved from pencil and paper, to typewriters and calculators, then to spreadsheets and accounting software. A new skillset that is becoming more important for nearly every aspect of business is that of big data analytics: analyzing large amounts of data to find actionable insights. This course is designed to help accounting students develop an analytical mindset and prepare them to use data analytic programming languages like Python and R.
This course is part of the Accounting Data Analytics Specialization
Offered By
About this Course
Skills you will gain
- Data Analysis
- Predictive Analytics
- Data Visualization (DataViz)
- Data Architecture
- coding
Offered by
University of Illinois at Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
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Syllabus - What you will learn from this course
INTRODUCTION TO THE COURSE
In this module, you will become familiar with the course, your instructor and your classmates, and our learning environment. This orientation module will also help you obtain the technical skills required to navigate and be successful in this course.
MODULE 1: INTRODUCTION TO ACCOUNTANCY ANALYTICS
In this module, you will learn how the accounting profession has evolved. You will recognize how data analytics has influenced the accounting profession and how accountants have the ability to impact how data analytics is used in the profession, as well as in an organization. Finally, you will learn how data analytics is influencing the different subdomains within accounting.
MODULE 2: ACCOUNTING ANALYSIS AND AN ANALYTICS MINDSET
In this module, you will learn to recognize the importance of making room for empirical enquiry in decision making. You will explore characteristics of an analytical mindset in business and accounting contexts, and link those to your core courses. You will then evaluate a framework for making data-driven decisions using big data.
MODULE 3: DATA AND ITS PROPERTIES
This module looks at specific characteristics of data that make it useful for decision making.
MODULE 4: DATA VISUALIZATION 1
In this module, you will learn fundamental principles that underlie data visualizations. Using those principles, you will identify use cases for different charts and learn how to build those charts in Excel. You will then use your knowledge of different charts to identify alternative charts that are better suited for directing attention.
Reviews
- 5 stars85.05%
- 4 stars13.14%
- 3 stars0.51%
- 2 stars0.51%
- 1 star0.77%
TOP REVIEWS FROM INTRODUCTION TO ACCOUNTING DATA ANALYTICS AND VISUALIZATION
The two lab sessions were useful and the speaker was well present himself and his points making it easy to understand him.
The course enables its learners to get a hands-on experience using tools to accounting data analytics and visualisation.
This is a really helpful course! I have learned not only about using Excel for accounting, but also the many functions of Excel.
Being the first online module I've ever taken to date, the content and videos far surpassed my expectations. Looking forward to more!
About the Accounting Data Analytics Specialization
This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting. This specialization also develops learners’ skills in machine learning algorithms (using Python), including classification, regression, clustering, text analysis, time series analysis, and model optimization, as well as their ability to apply these machine learning skills to real-world problems.
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