Please note:
To view the Summer 2026 Academic Calendar, go to www.sfu.ca/students/calendar/2026/summer.html.
Digital Transformation and Business Analytics
The graduate certificate in digital transformation and business analytics focuses on the use of digital technologies in business transformation. The certificate features programming in digital building block skills needed in the workforce such as analytical thinking, technological literacy, articulating data requirements and processes, applications of artificial intelligence, and using analytic, statistical and visualization techniques. This program is for aspiring functional analysts and data-driven decision makers.
Admission Requirements
Applicants must satisfy the university admission requirements as stated in Graduate General Regulation 1.3 in the 51社区黑料Calendar. For more information, please contact the Beedie School of Business.
Program Requirements
This program consists of course requirements for a minimum of 12 units. Course work may be substituted at the discretion of the dean and vice-provost of the Faculty of Graduate Studies.
Students must complete
The use of quantitative or statistical techniques in managerial decision-making. Students with credit for BUS 553 may not take this course for further credit.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
|
Gohram Gohram |
Oct 15 鈥� Nov 11, 2026: Tue, Thu, 2:00鈥�5:30 p.m.
|
SEGAL |
|
|
Gohram Gohram |
Nov 18 鈥� Dec 16, 2026: Mon, Thu, 6:00鈥�9:30 p.m.
|
SEGAL |
|
|
Srinivas Krishnamoorthy |
Sep 15 鈥� Sep 22, 2026: Tue, 7:00鈥�8:00 p.m.
Oct 6 鈥� Nov 2, 2026: Tue, 7:00鈥�8:00 p.m. Nov 16 鈥� Nov 23, 2026: Tue, 7:00鈥�8:00 p.m. |
VANCOUVER VANCOUVER VANCOUVER |
An introduction to the theories and practices of managing information technology. Uses case studies to analyze complex situations and develop skills necessary to select, deploy and use information systems. Students with credit for BUS 554 or BUS 621 or BUS 739 or BUS 756 may not take this course for further credit.
Introduces analytical knowledge that enables students to develop foundational knowledge of artificial intelligence (AI) and machine learning (ML), including the tools and methods of application and associated risks for use case identity across various business functions. Students with credit for BUS 774 under the title "AI in Business" may not take this course for further credit.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
|
Jie Mein Goh |
Sep 17 鈥� Nov 11, 2026: Thu, 6:00鈥�7:30 p.m.
|
VANCOUVER |
and a minimum of three units from the following
Builds on concepts introduced in BUS 706 to equip students with advanced skills in the use of data and models to make decisions. Focuses on stochastic, prospective, competitive, goal and productivity analytics. Prerequisite: BUS 706.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
|
Srinivas Krishnamoorthy |
Sep 15 鈥� Oct 13, 2026: Tue, Thu, 9:30 a.m.鈥�1:00 p.m.
|
SEGAL |
Data science tools like data wrangling, data analytics and visualization are introduced as they apply to areas such as marketing, human resources and operations management. Through a hands-on approach, students will learn various Python packages and Jupyter notebooks and how to use these tools to execute relevant data science techniques on complex data with a special focus on natural language processing, which is essential to understanding various textual information collected through various business processes.
Offers a comprehensive overview of advanced analytical and machine learning techniques used to predict customer behaviours such as patterns, responses to marketing initiatives, and customer loyalty.
Develops conceptual, analytics and decision-making skills related to generative AI use in marketing, with a focus on product development, design thinking and communication strategies.
Enterprise information systems, the relational database systems that underlie them, and creating value through competitive analytics. Develop an understanding of database querying and analytical applications to inspect, summarize, and transform data.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
|
Nilesh Saraf |
Nov 18 鈥� Dec 16, 2026: Mon, Thu, 6:00鈥�7:30 p.m.
|
VANCOUVER |
An exploration of financial and non-financial data using summary measures, predictive models for decision-making, and graphic visualizations.
* Students who complete BUS 706 and/or BUS 709 as MBA program requirements will select alternate certificate courses to complete 12 units. Students who complete BUS 706 and/or BUS 709 as certificate requirements and subsequently ladder into the MBA program will select alternate MBA electives to complete 58 units.
Laddered Pathway
The graduate certificate in digital transformation and business analytics can be completed as part of a laddered pathway in accordance with GGR 1.7.7c. Students who successfully complete the data management and business solutions micro-certificate will receive laddering credit for BUS 830 (3) and students who complete the analyzing and visualizing business data micro-certificate will receive laddering credit for BUS 831 (3) for a maximum of six units which can be applied towards the requirements of this graduate certificate.
Program Length
Students are expected to complete the program requirements within three terms.
Academic Requirements within the Graduate General Regulations
All graduate students must satisfy the academic requirements that are specified in the Graduate General Regulations, as well as the specific requirements for the program in which they are enrolled.