The University of Illinois - Deloitte Foundation Center for Business Analytics

Courses

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.

 

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.