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Business Intelligence from Web Data Analytics and Data Mining using R

This course is fully booked (no waiting list)

The business world today is an ultra-competitive environment where different organizations are scrambling to find competitive advantage through business intelligence. Organizations are inundated with a huge amount of data in most fields. This valuable data is often languishing in databases and data warehouses. The problem is that organizations do not have enough trained human analysts to turn this data into knowledge and intelligence.

This course provides an introduction to business intelligence process, including data collection, data exploration, data mining, data analysis, and model evaluation. It is designed to familiarize students with data collection, storage, analysis, and gleaming actionable information from this data. The course focuses on building the skills and competence of students by covering topics such as web data collection, open data, web analytics, data modeling, data mining development process, data preprocessing and exploration, analysis such as regression, k-nearest neighbor, decision trees, neural networks, clustering, and social network analysis.

Learning activities include lectures, case-based studies, actual web data collection, and demonstrations using the R software tool. The course does not expect students to have any prior computer programming skills nor heavy statistical analysis experience.

Business intelligence, including the process of exploring large data sets in order to bring out knowledge and significant information they may contain, will empower firms to uncover useful patterns and trends from existing data sources. Organizations will use business intelligence to guide their actions and the decision-making processes. This course is designed to allow students an introduction to this process.

Exam info and full course description

Exam info and full course description can be found in the course catalogue.

Admission Requirements

Course Specific:

To apply for the course you must either be enrolled in a bachelor's degree, have a bachelor's degree or have passed a qualifying entry examination.  

The use of a computer and basic computer knowledge is required for this course. We will be using the R programming tool in class. A heavy portion of the class will require students to learn and use the R programming language. 


Exchange students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about admission here.


Hirotoshi Takeda


Academic profile

Hirotoshi Takeda is Assistant Professor of Business Analytics and Information Systems at University of Southern Maine, USA.