M.Sc. in Computing and Data Analytics
Halifax Regional Municipality, Canada
MSc
DURATION
16 months
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
01 May 2026*
EARLIEST START DATE
Sep 2026
TUITION FEES
CAD 40,000 **
STUDY FORMAT
On-Campus
* all required documents must be received by the university by May 31, 2026
** Tuition and Fees are paid in four instalments at the beginning of each term (Sep 26, Jan 27, May 27, Sep 27)
Gartner projects that over 75% of enterprises started using AI by the end of 2024, driving a 5x increase in streaming data and analytics infrastructures. With these staggering levels of growth, there is a huge demand for data-savvy professionals with the ability to analyze, communicate, and innovate in a data-centric economy. Simultaneously, the demand for conventional computing expertise (computer programming, product development, quality engineering, etc.) also continues to rise.
Saint Mary’s Master of Science in Computing & Data Analytics (MSc CDA) is a graduate-level, 16-month professional program that focuses on using Generative AI (GenAI) to generate code and construct Business and IT solutions. Delivered across an interdisciplinary, industry responsive curriculum, the MSc CDA program has an impressive track-record for post-graduate employment.
MSc CDA’s primary focus is to develop highly qualified AI, computing and data analytics professionals who will drive innovation and organizational success. MSc CDA prepares students for rewarding careers through experiential learning opportunities and intensive industry interaction.
Benefits of the MSc CDA
- Our graduates continue to secure full time employment in computing/analytics roles through 3-year Canadian Post Graduate Work permits. The PG employment rate is nearly 100% since program inception
- Develop in-demand skills and practical experience applying industry-relevant technologies, methods, and data sets to solve real-world problems.
- Study with award-winning instructors from Saint Mary’s Faculty of Science and the Sobey School of Business, AACSB Accredited and the largest Canadian business school east of Quebec
- Build your professional network through interaction with industry instructors, paid internships, sponsored projects, industry workshops, expert guest speakers, hackathons, and special events. For recent cohorts, all students received funding during their residency period.
- Study in the heart of Halifax, Nova Scotia. Saint Mary's University campus is minutes from historic Halifax Harbour, vibrant downtown core, and beautiful beaches of the Atlantic Ocean.
Innovative, industry-responsive curriculum that incorporates lates technical trends:
- Focus on the full software development lifecycle and how AI and data analytics integrates into business decisions
- Generative AI: optimizing LLM performance
- End-to-End AI Solutions
- Ethical AI: bias, transparency, responsible model development
- Data Analytics: Augmented analytics, Practical machine learning, Predictive and prescriptive analytics, Edge Analytics, Automated ML (AutoML)
- Data-as-a-Service (DaaS)
- Big Data Governance: data quality, privacy, security, and compliance , cybersecurity (zero trust architecture; AI Driven security, digital forensics)
Program Requirements
Students must comply with the FGSR Program Requirements of the FGSR Academic Calendar. For an M.Sc. CDA, students must complete the following:
Twenty-four (24) credit hours in consecutive required courses over the first eight months:
| Code | Course title | Credits |
|---|---|---|
| MCDA 5510 | Software Development in Business Environment | 3 |
| MCDA 5520 | Statistics and Its Applications in Business | 3 |
| MCDA 5530 | UI/UX Design and Quality Engineering | 3 |
| MCDA 5540 | Managing and Programming Databases | 3 |
| MCDA 5550 | Web, Mobile, and Cloud Application Development | 3 |
| MCDA 5560 | Business Intelligence and Data Visualization | 3 |
| MCDA 5570 | Big Data and Information Technology Management | 3 |
| MCDA 5580 | Data and Text Mining | 3 |
| Select six credits of the following: | 6 | |
| MCDA 5585 | Master’s Project – System and Functional Analysis | |
| MCDA 5586 | Master’s Project – Implementation and Analysis of Results | |
| MCDA 5587 | Graduate Internship I | |
| MCDA 5588 | Graduate Internship II | |
| MCDA 5591 | Master's Thesis | |
| Total Credit Hours | 30 |
Note: Subject to the approval by the program coordinator, those students with significant prior professional experience and who will be completing two internship courses (Graduate Internship I (MCDA 5587) and Graduate Internship II (MCDA 5588)) may be able to replace up to six (6.0) credit hours of courses from:
| Code | Course title | Credits |
|---|---|---|
| MCDA 5510 | Software Development in Business Environment | 3 |
| MCDA 5520 | Statistics and Its Applications in Business | 3 |
| MCDA 5530 | UI/UX Design and Quality Engineering | 3 |
| MCDA 5540 | Managing and Programming Databases | 3 |
| MCDA 5550 | Web, Mobile, and Cloud Application Development | 3 |
| MCDA 5570 | Big Data and Information Technology Management | 3 |
| Select six credits of the following: | 6 | |
| MCDA 5585 | Master’s Project – System and Functional Analysis | |
| MCDA 5586 | Master’s Project – Implementation and Analysis of Results | |
| MCDA 5591 | Master's Thesis |
Project Option
The project option will be flexible enough to allow students to address one or two major computing and data analytics problems. Typically, the project will be divided into three stages:
- proposal
- prototype
- final product
Students will present their work from each stage in front of a supervisory committee consisting of the project supervisor and two other faculty members from the program. The program will draw from local industry professionals for project supervision. Project leaders from local software and data analytics organizations will be invited to co-supervise projects along with faculty members from the program. Faculty members will help ensure the academic requirements of the project are met, while industry professionals will help with the practical and applied aspects of the project work. Students can complete a new project within the context of their existing employment that implements principles of computing and data analytics as a part of the project option. Such a project must satisfy the requirements of the two project courses Master’s Project – System and Functional Analysis (MCDA 5585) and Master’s Project – Implementation and Analysis of Results (MCDA 5586).
Internship Option
Students will benefit from immersion at Computing and Data Analytics organizations through further industry exposure and opportunities for experiential learning. Each student will have an academic supervisor and an onsite supervisor. The program/university will award the final grade of pass or fail to ensure a consistent evaluation mechanism. Internship students will need to write and submit a report of their internship activities and measured achievements one month before the end of their internship. An academic supervisor will use the onsite supervisor's feedback and student's report to assess whether the scope of the reported work is sufficient to fulfill the requirements of the degree program. Students cannot use their existing employment as an internship option. They can complete a new project within the context of their existing employees to satisfy the requirements of the project option (please see project option for more details).
Thesis Option
The thesis option will enable students to acquire enhanced research skills that will prepare them to carry out independent research in their future careers. Students will research and write a thesis that is in an area of computing with a particular focus on data analytics. A topic is eligible for development into an M.Sc. CDA thesis if it identifies a complex problem(s) relevant to computing and data analytics, and is completed under the supervision of an approved faculty member.
Graduate Profiles
Jobs
MSc CDA focuses on career preparation for current and future computing and data analytics positions. Since inception, MSc CDA graduates have been hired for a wide range of exciting jobs:
- Data Analyst
- Software Engineer
- Full-Stack Developer
- Database and System Analyst
- Big Data Engineer
- BI Developer
- Manager, Business Analytics
- Data Scientist
- Data Quality Analyst
- Senior Solutions Architect
- Machine Learning Engineer
- IT Consultant
The range of organizations that hire our students is equally diverse and impressive:
|
|
|
|---|