What courses earn college credit?
The Institute for Statistics Education offers 29 courses that are eligible for college credit through ACE CREDIT^{®} (the American Council on Education’s College Credit Recommendation Service).
The ACE CREDIT College and University Network is a group of more than 2,200 higher education institutions that consider ACE credit recommendations for transfer to degree programs.
The following courses are eligible for college credit recommendation:
Course |
Methods of Assessment |
Credit Assessment |
Introductory Statistics for Credit 8 weeks |
The methods of assessment are quizzes, weekly homework assignments and a final examination, with a minimum passing score of 70 percent. | In the lower-division baccalaureate/ associate degree category, 3 semester hours in statistics. |
Biostatistics for Credit 8 weeks. |
The methods of assessment are quizzes, weekly homework assignments and a final examination with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in biostatistics. |
Anomaly Detection | The methods of assessment include quizzes, case studies, and a final project, with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in computer science, machine learning or artificial intelligence. |
Categorical Data Analysis | The methods of assessment are quizzes, case studies and weekly homework assignments with a minimum passing score of 70 percent. | In the upper division baccalaureate degree category, 3 semester hours in statistics. |
Cluster Analysis | The methods of assessment are weekly assignments and a final project with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in statistics or data mining. |
Customer Analytics in R | The methods of assessment are quizzes and case studies with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in statistics, data mining, or programming. |
Deep Learning | The methods of assessment include quizzes and case studies, with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in statistics, data mining or computer science. |
Financial Risk Modeling | The methods of assessment include quizzes, case studies and a final project, with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in financial risk management, financial econometrics or applied statistics. |
Forecasting Analytics | The methods of assessment are homework assignments and a final project with a minimum passing score of 70 percent. | In the lower-division baccalaureate/associate degree category, 3 semester hours in forecasting analytics, data mining, or data science. |
Interactive Data Visualization | The methods of assessment are quizzes, weekly homework assignments and a final project with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 2 semester hours in computer science, computer information systems, or information technology. |
Integer & Nonlinear Programming and Network Flow | The methods of assessment are weekly homework assignments with a minimum passing score of 70 percent. | In the upper division baccalaureate degree category, 3 semester hours in operation research, computer programming, statistics or computer information systems. |
Matrix Algebra Review | The methods of assessment are quizzes and case studies with a minimum passing score of 70 percent. | In the lower-division baccalaureate/associate degree category, 3 semester hours in mathematics. |
Natural Language Processing | The methods of assessment are weekly homework assignments, class posts, and short answer questions with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 2 semester hours in computer science, computer information systems, or cyber security. |
Introduction to Network Analysis | The methods of assessment are weekly homework assignments and a final project with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in computer science or network analysis. |
Optimization – Linear Programming | The method of assessment is weekly homework assignments with a minimum passing score of70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in mathematics or business management. |
Persuasion Analytics and Targeting | The methods of assessment include quizzes, case studies, and a final project, with a minimum passing score of 70 percent. | In the upper-division baccalaureate/associate degree category, 3 semester hours in computer science or data mining. |
Predictive Analytics 1 –Machine Learning Tools | The methods of assessment are weekly homework assignments, a final project, and class posts with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in predictive analytics, data mining, or business analytics. |
Predictive Analytics 2 – Neural Nets and Regression | The methods of assessment are weekly homework assignments, a final project, and multiple-choice exams with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in business analytics, predictive analytics, business analytics or data mining. |
Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules | The methods of assessment are a final project, multiple-choice examinations, and class posts with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in business analytics, predictive analytics, or data mining. |
Introduction to Python for Analytics | The methods of assessment are weekly homework assignments and a final project with a minimum passing score of 70 percent. | In the lower-division baccalaureate/ associate degree category, 3 semester hours in computer information systems, statistics, or programming. |
R Programming – Introduction 1 | The methods of assessment are weekly homework assignments with a minimum passing score of 70 percent. | In the lower-division baccalaureate/ associate degree category, 3 semester hours in computer programming, computer science, or information systems. |
R Programming – Introduction 2 | The methods of assessment are weekly homework assignments with a minimum passing score of 70 percent. | In the lower-division baccalaureate/ associate degree category, 3 semester hours in computer programming, computer science, or information systems. |
R Programming – Intermediate | The methods of assessment are weekly homework assignments and a final exam with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in computer science, computer programming, information systems or statistics. |
Regression Analysis | The methods of assessment are quizzes, a final project, and weekly homework assignments with a minimum passing score of 80 percent. | In the graduate degree category, 3 semester hours in statistics or applied regression analysis. |
Risk, Simulation and Queuing | The methods of assessment are quizzes and weekly homework assignments with a minimum passing score of 80 percent. | In the graduate degree category, 3 semester hours in statistics or decision science. |
Spatial Statistics with Geographic Information Systems | The methods of assessment are weekly homework assignments and a final project with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in spatial statistics, geospatial analysis or statistics. |
SQL and R – Introduction to Database Queries | The methods of assessment are weekly homework assignments with a minimum passing score of 70 percent. | In the upper-division baccalaureate degree category, 3 semester hours in SQL queries, computer science or information systems. |
Survival Analysis | The methods of assessment are weekly homework assignments and a final project with a minimum passing score of 80 percent. | In the graduate degree category, 3 semester hours in statistics or advanced biostatistics. |
Text Mining | The methods of assessment are weekly homework assignments with a minimum passing score of 70 percent. | In the lower-division baccalaureate/associate degree category, 3 semester hours in computer science, information systems or cyber security. |
- Biostatistics 1 – For Medical Science and Public Health
- Biostatistics 2 – For Medical Science and Public Health
- Biostatistics for College Credit
- Categorical Data Analysis
- Cluster Analysis
- Financial Risk Modeling
- Forecasting Analytics
- Interactive Data Visualization
- Introduction to Network Analysis
- Logistic Regression
- Introduction to Statistics for College Credit
- Natural Language Processing
- Optimization – Linear Programming
- Predictive Analytics 1 – Machine Learning Tools
- Predictive Analytics 1 – Machine Learning Tools – with Python
- Predictive Analytics 1 – Machine Learning Tools – with R
- Predictive Analytics 2 – Neural Nets and Regression
- Predictive Analytics 2 – Neural Nets and Regression – with R
- Predictive Analytics 2 – Neural Nets and Regression with Python
- Predictive Analytics 3 – Dimension Reduction, Clustering and Association Rules
- Predictive Analytics 3 – Dimension Reduction, Clustering and Association Rules – with R
- Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules with Python
- Python for Analytics
- R Programming – Intermediate
- R Programming – Introduction 1
- R Programming – Introduction 2
- Regression Analysis
- Risk Simulation and Queuing
- Sentiment Analysis
- Spatial Statistics for GIS – Using R
- Statistics 1 – Probability and Study Design
- Statistics 2 – Inference and Association
- SQL – Introduction to Database Queries
- Survival Analysis
- Text Mining Using Python