Certificate Information

This certificate will provide a strong foundation in analytics, tools, and statistics. It is targeted to individuals who need to use data analytics, big data, and predictive analytics to optimize performance at a variety of levels in a wide range of sectors or are employed in a related field such as data warehousing, data management, IT, etc. and need to acquire the necessary credentials for career promotion or other professional enrichment.

Upon successful completion of this certificate, graduates will be prepared to take the Institute for Operations Research and the Management Sciences (INFORMS) Certified Analytics Professional (CAP®) exam to become certified professionals in this burgeoning field. For more information about the CAP® designation, visit the INFORMS CAP® page.

For detailed certificate and program information, please visit www.ryerson.ca/ce/bigdata.

See more courses and programs relating to Business, Management, and Economics and Computer and Information Technology.

Admission Criteria

Eligible applicants must have the following:

OSSD with six Grade 12 U credits, including Grade 12 U credits in English, Mathematics (Advanced Functions and one of either Calculus and Vectors or Data Management), and Science (Biology or Chemistry or Physics);
M credits with a minimum grade of 70 percent or equivalent academic status
Mature student status with four years of relevant professional experience AND the approval of the academic coordinator.

Note: Applicants should contact Anne-Marie Brinsmead, Program Director, at a2brinsm@ryerson.ca or at 416.979.5000, ext. 2665 or attend a Program Open House.

Undergraduate students wishing to pursue a continuing education certificate program should be aware of possible restrictions; please refer to Curriculum Advising for complete details.

Program Open House

Students who have questions about the admission criteria and/or would like to know more about this certificate are invited to attend a Program Open House. Please see Open House for dates, times, and location.

Certificate Requirements

The successful completion of six courses, with a cumulative grade point average of 1.67 or higher, is required for the certificate.

Certificate Registration

Students may be registered in only one certificate program at any one time. To allow maximum flexibility in crediting external courses and/or courses previously taken at Ryerson, students should register in the certificate at the beginning of their first course (see also Courses and Programs FAQ). For complete details on the advantages of early registration, registration deadlines, and Transfer Credit restrictions, all students should read Registration in a Certificate Program.

Requirements for Graduation

To graduate, you must successfully complete the published certificate curricula from the year you registered in the certificate. Certificate requirements must be completed within six years from the time you were first admitted into the certificate program. In some circumstances, certificate requirements may change, resulting in courses no longer being available. In such cases, Course Substitutions/Directives may be requested. Also, you must apply on RAMSS to graduate, prior to the appropriate application deadlines (see Important Dates). For complete details, all students should read Graduation.

Recommended Sequence

Students are advised to take the courses in the following sequence; however, CIND 123, CIND 119, and CIND 110 may be taken concurrently. CMTH 642 and CIND 719 may be taken concurrently. CKME 136 may not be taken until the previous five Required Courses have been successfully completed.

CIND 123
CIND 119
CIND 110 OR CCPS 270
CMTH 642
CIND 719
CKME 136

Required Courses

Students may only select one of CIND 110 or CCPS 270.

CCPS 270   Computer Science:  Data Access and Management
CIND 110   Industrial Engineering:  Data Organization for Data Analysts
CIND 119   Industrial Engineering:  Introduction to Big Data
CIND 123   Industrial Engineering:  Data Analytics: Basic Methods
CIND 719   Industrial Engineering:  Big Data Analytics Tools
CKME 136   Mechanical Engineering:  Data Analytics: Capstone Course
CMTH 642   Mathematics:  Data Analytics: Advanced Methods

Note to registered certificate program students
Required Courses
CKCS 110 deleted.
CCPS 270 added.

Fast Track in Data Analytics, Big Data, and Predictive Analytics

Participants in the Data Analytics Fast Track (CKME 999) can complete 5 of the 6 courses in the Certificate in Data Analytics, Big Data, and Predictive Analytics in three months and access specialized material and individualized instructor support. The sixth course, Data Analytics: Capstone Course (CKME 136), is completed online in a subsequent academic term of the student's choosing.