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Data analytics curriculum for the classroom

University of Illinois-Deloitte Foundation Center for Business Analytics

​The University of Illinois-Deloitte Foundation Center for Business Analytics provides free online data analytics curriculum to help advance business education.

University of Illinois-Deloitte Foundation Center for Business Analytics

The University of Illinois-Deloitte Foundation Center for Business Analytics (“The Center”) was launched through a grant from the Deloitte Foundation to advance business analytics education by helping provide students with the data knowledge, skills, and abilities needed to become highly-trained business leaders. With curriculum designed by faculty at University of Illinois, Gies College of Business, The Center is a collaborative effort that brings together representatives from all of Deloitte’s businesses and the Deloitte Foundation to provide guidance through a practice lens and strengthen the connection between academia and the profession.

The modern world of accounting and business is changing rapidly. Data is everywhere, and that data is constantly changing. Accounting and business professionals use business analytics to answer complex questions. The data analytics curriculum can help prepare students to use data effectively today, but also help prepare them for a dynamic future.

Symposia, Workshops, Presentations, and Conferences

The Center offers a variety of events that bring together scholars, practitioners, and regulators who present and provide feedback on timely topics.

 Auditor Risk Assessment: Hands-On Webinar Teaching Orientation

This 8-module Case Study can be used in Audit, Analytics or Risk courses to offer students simulated real-life audit experiences in the classroom. The Case Study reflects both the technical and soft skills future auditors will likely need and captures the many different aspects of the audit, from receiving a report from the client, to analyzing data, asking questions of the client, evaluating support, and documenting a risk assessment. The exercises relate to day-to-day activities that auditors perform to complete an audit, such as the creation of data visualizations, analyzing those visualizations, documenting a risk assessment, following-up with the client, and more.
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First course in Foundations of Data Analytics

The first course in Foundations of Data Analytics, rreleased in April 2019, is free, online and accessible to anyone who wants to leverage it for their educational mission. Each module contains multiple lessons and was designed by faculty at University of Illinois, Gies College of Business. The course consists of 60 hours of curriculum broken up into eight modules that can be used on their own or integrated into existing curriculum:

  • Module #1: Foundations (6 hrs, 30 min)
  • Module #2: Introduction to Python Programming (8 hrs, 30 min)
  • Module #3: Introduction to Data Analysis (6 hrs, 30 min)
  • Module #4: Statistical Data Analysis (8 hrs, 30 min)
  • Module #5: Introduction to Visualization (6 hrs, 30 min)
  • Module #6: Introduction to Probability (7 hrs, 30 min)
  • Module #7: Exploring Two-Dimensional Data (8 hrs, 30 min)
  • Module #8: Introduction to Kernel Density Estimation (7 hrs, 30 min)

Second course in Foundations of Data Analytics

The eight modules in the second course in Foundations of Data Analytics, released in December 2019, will build a practical foundation for machine learning by teaching students basic tools and techniques that can scale to large computational systems and massive data sets. Topics include algorithms, overfitting and regularization, clustering, anomaly detection, and more:

  • Module #1: Introduction to Machine Learning
  • Module #2: Fundamental Algorithms
  • Module #3: Practical Concepts in Machine Learning
  • Module #4: Overfitting and Regularization
  • Module #5: Fundamental Probabilistic Algorithms
  • Module #6: Feature Engineering
  • Module #7: Introduction to Clustering
  • Module #8: Introduction to Anomaly Detection

Data Analytics Foundations for Accountancy I

Data Analytics Foundations for Accountancy I, released in June 2020, introduces students to the basic concepts needed to complete common data analytic tasks in accountancy and business in general. Students will learn to develop data analytic scripts by using the Python programming language and the standard data analytic Python modules, including Pandas, NumPy, SciPy, Matplotlib, and Seaborn:

  • Module #1: Foundations
  • Module #2: Introduction to Python
  • Module #3: Introduction to Python Programming
  • Module #4: Python Programming
  • Module #5: Introduction to Data Persistence
  • Module #6: Introduction to Data Analysis
  • Module #7: Introduction to Visualization
  • Module #8: Exploring Two-Dimensional Data

Data Analytics Foundations for Accountancy II

Data Analytics Foundations for Accountancy II, builds upon concepts introduced in the first course to enable students to obtain, explore, and analyze richer and more complex data sets. Students will first learn how explore and analyze multi-dimensional data sets, before learning how to obtain text data embedded within websites and how to analyze text data by using standard Python techniques and regular expressions:

  • Module #1: Applied Data Analytics
  • Module #2: Introduction to Text Analytics
  • Module #3: Introduction to Data Persistence
  • Module #4: Introduction to Python and Databases
  • Module #5: Introduction to Probability
  • Module #6: Introduction to Time Series Data
  • Module #7: Introduction to Time Series Analysis
  • Module #8: Introduction to Density Estimation

Content and materials were designed by faculty at University of Illinois, Gies College of Business. To access these courses, please visit the Courses in Foundations of Data Analytics page on The Center's website. For more information on the Center, contact Kristy Chernick.

Case Studies

Data Analytics Case Studies
The Center offers three case studies developed by faculty at the University of Illinois’ Gies College of Business which are designed to identify and address applications of data analytics in today’s business environment. The cases can be inserted directly into data analytics curriculum and offer students the opportunity to use data in important and practical ways.

Topics covered in the case studies include customer segmentation, introduction to databases for accountants, data analysis, and web scraping using robot process automation.

Mini-Case Studies
The Center has also released five mini-case studies, which are designed to build up students’ understanding of a management control system (MCS) and their data analytics skills in investigating MCS-related issues. The five mini-case studies focus on the following areas:

Control Tools

  1. Holding people accountable for results – “Results control”
  2. Identifying, selecting, hiring, promoting the right employees – “Personnel control”
  3. Promoting the right type of cultures and norms – “Cultural control”

Data Analytics Skills

  1. Operationalizing a big control issue and disaggregating into specific data questions
  2. Properly asking managers or employees to answer these specific questions
  3. Designing a data structure to collect archival records to answer specific questions
  4. Critically evaluating the meaning of the data pattern
  5. Clearly communicating your results to decision makers in the organization

Content and materials were designed by faculty at University of Illinois, Gies College of Business. To learn more and access the case studies, visit the Case Studies page on The Center’s website. For more information on the Center, contact Kristy Chernick.

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