Organizations collect masses of data. Accounting professionals who know how to uncover, analyze, and communicate insights from those data to drive decision-making are in high demand. In the Graduate Certificate in Accounting Data Analytics program, you’ll develop standout data analytics capabilities, and perform at the leading edge in the fast-changing field of accounting.

You’ll get the very latest from some of the best faculty in the world, teaching at the master’s level. Gies College of Business at the University of Illinois is consistently ranked among the top three accounting programs in the country and is a leader in data analytics.

This certificate is designed for:

  • Accounting professionals looking to update skills
  • Business leaders without accounting backgrounds
  • Learners who are preparing for the CPA exam

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Start Dates
August, October, 
January or March

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Duration
8 Months

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Program Fees
$5,960 - $10,200 USD
(Depending on electives)

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Credit Hours
12

Learn leading-edge analytics skills

You’ll develop exceptional accounting data analytics capabilities, including the ability to:

  • Frame problems in ways that can be answered by data and produce actionable results
  • Create interactive visualizations in Excel and Tableau to explore data, identify patterns and relationships, and communicate findings
  • Apply Python skills for assembling business data, including financial statement data, stock data, loan data, point-of-sale data, and more
  • Share results within Jupyter Notebook, a popular development environment for data analytic software such as Python and R
  • Use fundamental programming skills, such as mathematical operators, functions, conditional statements, and loops using Python
  • Conduct statistical analyses for quantifying patterns and relationships observed in the data

Course structure and format

This fully online program is designed to fit the schedules of working professionals.

  • Weekly live classes and office hours with top faculty
  • Self-paced, downloadable course material on Coursera
  • Group discussions and projects with peers around the globe
  • Immediately applicable graduate-level coursework

 




Courses details

You can complete the program in as few as eight months. This certificate is comprised of two required courses and eight credit hours of additional electives. This translates into a commitment of about ten hours per week.

Required courses

The following two courses are required for this graduate certificate.

ACCY 569: Data Driven Decisions in Accounting

This course prepares students to use analytic software to explore, visualize, and statistically analyze accounting data. It first introduces students to the need for analytics in accounting by sampling problems from different accounting domains. Students then learn to frame problems in a way that can be answered by using data, and how to structure data so that it’s ready to be analyzed.

Students create interactive visualizations in Excel and Tableau to examine data, identify patterns and relationships in the data, and then communicate the findings. This course also introduces students to statistical analyses (i.e. regression and clustering) for quantifying patterns and relationships that are observed in the data. Finally, this course introduces accounting students to programming via macros and the VisualBasic editor in Excel to automate data preparation and data analyses.

ACCY 576: Data Preparation for Accounting

This course focuses on developing Python skills for assembling business data, taught within the context of multiple accounting settings (e.g., financial statement data, stock data, loan data, point-of-sale data, etc.). The first half of the course uses an integrated development environment to automate data analytic tasks. We discuss how to manage code and share results within Jupyter Notebook, a popular development environment for data analytic software like Python and R. We then review some fundamental programming skills, such as mathematical operators, functions, conditional statements and loops using Python software.

The second half of the course focuses on assembling data for machine learning purposes. We introduce students to Pandas dataframes and Numpy for structuring and manipulating data. We then analyze the data using visualizations and linear regressions. Finally, we explain how to use Python for interacting with SQL data.

Elective courses

Learners should select eight hours of elective courses from the list below.

ACCY 577: Machine Learning for Accounting

This course introduces machine learning algorithms and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses feature importance and model optimization.

This course provides an entry point for students to be able to apply proper machine learning algorithms on business related datasets to solve various problems. By end of the course, combined with the skills learned from ACCY 576, students should be able to complete an entire data analytics process with Python.

ACCY 578: Accounting Analytics Applications

In this course, you can develop your knowledge regarding the roles, methods, and implications of business and data analytics in accounting via real-world applications of fundamental and advanced analytics principles.

Application opportunities span multiple areas of accounting, including audit, fraud identification and detection, financial accounting, and managerial accounting. After engaging in this course, you’ll possess a foundational understanding of the role of business and data analytics in accounting and be able to apply this knowledge to real-world business use cases.

  • 1 Credit Hour, 4-Week Course, Starts in October
  • May be repeated when topics vary for up to 4 credit hours. This course will also be offered in October, November, March, and April.
MBA 563: Data Toolkit: Business Data Modeling & Predictive Analytics

The emphasis of this course is placed on developing a business analytic mindset. You will then be exposed to various tools to perform tasks including extracting, transforming and loading (ETL) data to conduct exploratory data analytics (EDA). These tools are Power BI, R, and Alteryx. In addition, you will learn different machine learning algorithms but also develop the ability to evaluate and select the right algorithms for the right circumstances and use Notebooks to communicate results with others.  

Please note, Because Power BI and Alteryx are only built to run on a Windows operating system, you will need to either have administrative access to a Windows machine, or install additional software, such as Virtual Box, so that you can emulate a Windows operating system on your Mac or Linux operating system.

To be successful in this course, you must be comfortable with R concepts and commands. It is recommended to complete the Introduction to Business Analytics with R MOOC before beginning this course.

MBA 564: Applying Data Analytics in Marketing

In this course, you’ll focus on marketing analytics techniques and how to use those techniques to solve real-world marketing problems. You will cover topics including t-tests, natural language processing, and network analysis, and more. You will use R programming to learn key concepts, including the four tools of marketing analytics.

To be successful in this course, you must be comfortable with R concepts and commands. It is recommended to complete the Introduction to Business Analytics with R MOOC before beginning this course.

MBA 564: Applying Data Analytics in Accountancy

In this course, you’ll be introduced to cutting-edge technologies being used in business, particularly in accounting. You’ll cover analytics techniques including natural language processing and robot process automation. You will gain an increased familiarity to technologies including blockchain, cyber security, and process mining.

Please note, Completion of this course requires downloading and using free versions of the Alteryx applications, both of which are only compatible with Windows Operation System (i.e. Windows 10). Therefore, to complete this course, you must have administrative access to a computer with Windows operating system installed. Alternatively, you may use a free virtual desktop environment that contains all the software requirements.

To be successful in this course, you must be comfortable with R concepts and commands. It is recommended to complete the Introduction to Business Analytics with R MOOC before beginning this course.

MBA 565: Infonomics

This course provides a non-technical perspective on and methods for monetizing, managing, and measuring information as if it were any other kind of corporate asset.

How to apply

To apply for a graduate certificate program, you'll need to start an online application through the University of Illinois Graduate College.

The following items are required for your application:

  • Bachelor’s degree: Unofficial transcripts are acceptable.
  • Professional resume: This should include personal information (name, address, telephone number, and email address), educational background, work experience (start and end dates for each position and a brief description of responsibilities), educational training, professional associations, and leadership experiences. Please limit your resume to two pages. 
  • Brief personal statement: A 500-word or less statement describing your interest in the certificate program.
  • English proficiency scores (international students only): If you are a non-native English speaker, you will need to upload your TOEFL or IELTS scores directly to your application. Review the Graduate College’s English proficiency requirements for more details on possible exemptions.


Continue your learning journey

Stack your credit hours into a graduate business degree


If you are interested in continuing your education with Gies, the twelve credits you earn in the Accounting Data Analytics Graduate Certificate can be directly applied to one of three Gies online master's degree - the iMBA, iMSA, or iMSM. 

    Looking for CPE Credits? This graduate certificate qualifies for credit toward continuing professional education requirements. Upon completion of the course, you can request CPE credit by submitting this online form.

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