Data Analytics: Model Design


Course description

In the third course of the Business Intelligence and Data Analytics Certificate program, you will gain the knowledge and ability to design, build and report on a data analytics model as part of a case study data analytics project. Using standard industry informatics tools, you will identify, scrape and prepare data to use in the design and creation of descriptive and diagnostic models, including techniques for identifying (and removing or imputing) missing data.

Upon completion of this course, you will be able to:

  • explore and practice with a selection of data analytics techniques from over 60 machine learning packages, including artificial intelligence and deep learning;
  • design and build data analytics descriptive and diagnostic models as part of a business solution for a case study problem;
  • identify relevant data sources and use advanced R techniques to wrangle data from several digital and digitized sources to support a data analytics project; and
  • use advanced R techniques to prepare a data analytics report, including a versioned metadata document in which you will create a modified conceptual data model for a case study problem.

How to register

This course is part of the Business Intelligence and Data Analytics program.

To register in the courses, you must apply to and be accepted into the program.

Please contact the Program Assistant at or 250-472-5442 for further information.

Additional course details

Blended delivery

In-Class Requirement

The blended delivery model incorporates online learning with two days of on-campus classes. These classes at the beginning of the course allow  students to become acquainted with UVic, faculty and fellow students.

While on campus, students will:

• begin to engage in core elements of the program;
• develop skills essential for success in the related field of data science;
• consolidate learning acquired during the program; and
• benefit from interaction with the instructor and other learners.

Online learning

The online learning portion of this course expands upon the conceptual introductions offered during the on-campus classes, allowing participants to practice skills and expand their knowledge base. The online portion delivers much of the theoretical and information-based material in the program. This material is applied to case study exercises undertaken by teams of students within each course.

The online portion of the program takes place over the internet, using a learning management system known as Moodle. The Moodle site for this course will contain discussion forums and readings. At their convenience, students work through the requirements of the course (although there are ‘real time’ deadlines for assignments, etc).

Students will study online for approximately four weeks, and will be required to spend approximately 15 hours per week on coursework. This may vary at times throughout the course and from student to student. During the first course, the amount of time required may be higher, as students familiarize themselves with our online learning technologies.

Required equipment/software

Hardware and Operating Systems

  • Internet connection (DSL, LAN, or cable connection desirable)
  • Course Moodle site, URL will be provided
  • Laptop with administrator privileges, and power cable
    • ​CPU: i5/i7 or equivalent
    • 16GB/32GB RAM
    • 300MB/20GB free hard disk space
    • Wi-Fi capable
    • 32 bit/64bit OS
    • Dedicated GPU with on-board RAM (the more the better, but there is no heavy graphics usage)


  • R - free unlimited use under open source agreements
  • RStudio – free unlimited use under open source agreements
  • MS Office (Word, Excel) or equivalent - for example Open Office (free unlimited use under open source agreements); PowerPoint or equivalent would be useful, but is not necessary
  • Web Browser (Chrome recommended)
  • DIA or Visual Paradigm CE or suitable diagramming software (consult instructor)
  • Anti-virus scanner

Course text

  • No textbook required


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