The University of Illinois - Deloitte Foundation Center for Business Analytics

Courses

First Course in Foundations of Data Analytics

The First Course in Foundations of Data Analytics consists of 60 hours of curriculum broken up into eight modules that can be used on their own or integrated into existing curriculum. Each module contains multiple lessons, which each include a short video and assigned reading.

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

Please complete our brief registration form to access the curriculum. Access to the curriculum will be emailed to you soon after you complete the registration form.

We’ve also included an Instructor’s Guide to provide more detailed information about the content and objectives for the course.

If you have additional questions or would like to provide feedback, email us.

Second Course in Foundations of Data Analytics

The Second Course in Foundations of Data Analytics 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. Each module consists of multiple lessons, which each contain a video explaining the lesson content, external reading(s), and included course Jupyter notebooks. Each module also includes a quiz (or assessment) that tests basic mastery of the lesson contents, and a programming assignment that tests synthesis of the lesson contents.

  • 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

Please complete our brief registration form to access the curriculum. Access to the curriculum will be emailed to you soon after you complete the registration form.

We’ve also included an Instructor’s Guide to provide more detailed information about the content and objectives for the course.

If you have additional questions or would like to provide feedback, email us.

Data Analytics Foundations for Accountancy I

Data Analytics Foundations for Accountancy I 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

Please complete our brief registration form to access the curriculum. Access to the curriculum will be emailed to you soon after you complete the registration form.

We’ve also included an Instructor’s Guide to provide more detailed information about the content and objectives for the course.

If you have additional questions or would like to provide feedback, email us.

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

Please complete our brief registration form to access the curriculum. Access to the curriculum will be emailed to you soon after you complete the registration form.

We’ve also included an Instructor’s Guide to provide more detailed information about the content and objectives for the course.

If you have additional questions or would like to provide feedback, email us.