Applied Computing

Master of Science Full-time School of Computing and Academic Studies

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Info sessions

Explore all upcoming BCIT info sessions.

Blogs

Should we trust AI? Dr. Aaron Hunter, BCIT Mastercard Chair in Digital Trust explores this increasingly relevant question during his 18-minute talk at TEDxAbbotsford.

Computing faculty Dr. Michal Aibin recently secured a two-year grant to advance drone and AI technology for detecting forest fire risk and predicting potential fire locations. “The ultimate goal of our work is to help build safer, more resilient communities and ecosystems.”

Dr. Borna Noureddin developed the MSc in Applied Computing’s course in Human-centered Computing. Learn more about his work on how to ensure that technology makes the world better.

Overview

The Master of Science Degree in Applied Computing gives you in-depth computing knowledge to solve complex real-world problems across industries and sectors. Through an interdisciplinary and rigorous full-time curriculum, you’ll be equipped to provide technical leadership in a professional setting or pursue further academic study.

About the program

Applied computing integrates information technology, computer science, and industry. You’ll take courses in core computing, and you will have the opportunity to work in an application area in another discipline. You’ll develop a deep understanding of how advanced computing, tools, and computational methods can be applied in practice to overcome challenges and create efficiencies.

The program employs a cohort model, with the same group in all courses. This allows you to work through the program together, sharing your experience and expertise and building industry connections that will last long after you graduate
1 intake: September
4 15-week terms, normally completed over two academic years full time
First year with two terms , delivered in-person, including:
- Algorithm analysis
- Human-centered Computing
- Machine Learning (ML) & Artificial Intelligence (AI)
- Data Science
- Cybersecurity
- Research methods
Second year on thesis path or internship & project path
Based on BCIT Burnaby Campus, and possibly the Downtown Campus or field locations where appropriate.
You’ll be uniquely qualified to apply your knowledge and skills in various areas, such as:
- computational science
- rehabilitation engineering
- building science
- biotechnology
- autonomous vehicles
- sustainability
- smart micro-grids
- social impacts of technology
- network security
- an approved project area of your choosing based on your professional background

See the Program Details to learn more.

Who it’s for

This degree might be for you if you:

Are inspired to maximize the societal benefit of computing by solving real-world issues
Would like to apply your skills in industry after graduation, but might also consider applying for a PhD
Are looking for a cohort-based program where you’ll work with other students to share problem-solving skills and approaches, as you would in a work setting
Have an applied problem you believe could be improved through computing
Would like to study with computing faculty, application experts outside of computing, and industry partners

Students will also have the opportunity to undertake directed studies with a supervisor in a different department to gain additional knowledge in a specific application area.

Please review the Entrance Requirements to learn more.

What grads can do

Provide technical leadership for software/system development teams
Demonstrate deep, critical knowledge and understanding of advanced topics in computing science
Analyze how computing systems and software can be used in practical applications and interdisciplinary fields
Design, develop, and implement innovative solutions to industry problems with consideration to relevant ethical, social and environmental issues
Explain and advocate for applied computing solutions to specialist and non-specialist audiences in both business and academic settings

See the Graduating & Jobs page to learn more.

Did you miss our Info Session? Please see the recording from October 2024:

BCIT Master of Science in Applied Computing | Info Session

Entrance Requirements

Application processing

Applications are accepted:

First round: October 1* to January 31*
Second round: February 1* to March 31*
Third round: April 1* to July 31*
International applicants must hold a valid BCIT study permit to apply to the third round.

*or next business day

Indigenous applicants: Read about Indigenous student support available for BCIT Computing programs.

Entrance requirements

Competitive entry: Two-step process

Admission to the program is competitive, with preference given to applicants with a combination of:

Academic grades above the minimum
Relevant industry experience

Step 1: Meet the following entrance requirements:

English language proficiency: Graduate Studies – English Studies 12 (67%) or equivalent

One of the following entry requirements:
Option 1: standard entry
- Post-secondary education: A bachelor’s degree in computer science or equivalent, such as BCIT’s Bachelor of Science in Applied Computer Science, with a minimum GPA of 2.8 out of 4.0 (70%) based on the final 30 credits of undergraduate study at BCIT or equivalent (e.g., one year of full-time studies).
Option 2: alternate entry
Alternate entry is for applicants who don’t have a bachelor's degree in computer science and may need to take bridging courses before being accepted to the program. Applicants are required to have the following:
- Post-secondary education: bachelor's degree with a minimum GPA of 3.0 out of 4.0 (73%) in another discipline based on the final 30 credits of undergraduate study, with significant knowledge of computing through formal education and/or work experience.
- Completed Pre-entry Assessment form [PDF]: submit the form to CompMSc@bcit.ca. The program area will review your pre-entry assessment and bridging courses may be required before applying to the program. Bridging courses will be recommended from existing COMP courses at BCIT, although transferable course work from other recognized Canadian post-secondary institutions may also be used. Applicants may be requested to send additional documents or meet with the program area.

Complete the following form for submission with your online application:
- Mandatory Applicant Questionnaire [PDF]: This form will be used with other entrance requirements in the competitive selection for the program.

Applicants who have completed post-secondary studies outside of Canada, the United States, the United Kingdom, Australia or New Zealand will require a comprehensive evaluation of their credentials by the International Credential Evaluation Service (ICES). Credential evaluation reports from other Canadian services may be considered.

Step 2: Department Review

All complete applications will be reviewed by the Graduate Program Committee and ranked competitively, and applicants will be offered admission accordingly. Only complete applications with all the required supporting documentation will be evaluated for admission consideration to the program.

Recommended for success

Applicants with a sufficient knowledge base in computer science will be best positioned for success in this program. This may include students who have studied information and communications technology (ICT), engineering, physics, mathematics, applied sciences, or other areas where they have been exposed to computing, information technology, and programming concepts.

International applicants

This program is available to international applicants.

Study permit: A valid BCIT study permit is required prior to starting the program.

Students enrolled in the Project & Internship Path of this program must complete the mandatory work component to qualify for graduation. A co-op work permit is required prior to starting the work component.

Apply to program

To submit your application:

Include proof of meeting all entrance requirements.
Convert all transcripts and supporting documents to PDF files.
Have a credit card ready to pay the application fee.

Apply Now

Learn more about how to apply

Scheduled Intakes

September each year.

Costs & Supplies

Tuition fees

Use our tuition estimator to find tuition and fees for this program.

For more information on full-time tuition and fees, visit:

Books & supplies

Each term: $450
(general estimated cost, subject to change).

Students are expected to have their own laptops.

Financial assistance

Financial assistance may be available for this program. For more information, please contact Student Financial Aid and Awards.

Courses

Class hours

9:00 am to 4:00 pm.

Program matrix

Level 1 (15 weeks – September to December)			Credits
	COMP 9060	Applied Algorithm Analysis In this course, students will develop the ability to analyze, select, and design advanced computer algorithms. In particular, students will analyze the time and space complexity of programs, solve difficult programming problems using algorithmic techniques, and prove that their solution is correct. The emphasis will be on developing new algorithms, optimization based on constraints, and implementing real-world solutions. Topics covered may vary each term. Prerequisite(s): No prerequisites are required for this course. course outline	3.0
	COMP 9170	Data Science* This course provides a foundation to conduct predictive analytics through a focus on each stage of the data modelling life cycle. Practical lab and assignment work include data exploration and preparation, development of continuous variable and classifier predictive models with statistical and machine learning algorithms. Evaluation metrics and model validation techniques are emphasized to provide balanced views of model strengths and weaknesses. Prerequisite(s): No prerequisites are required for this course. course outline	3.0
	COMP 9200	Applied Research Methods This course introduces principles and procedures of standard research methodologies in the context of an interdisciplinary computing environment. It introduces the students to theories, paradigms and frameworks in computing, and the role and importance of models, theories and conceptual frameworks. The course also exposes students to quantitative and qualitative research methods such as surveys, interviews, experiments, case studies, grounded theory analysis and ethnography. Students also practice using inference as well as deductive and inductive reasoning, assessing the reliability and validity of data, and examining critically the assumptions, claims and methodology of existing literature. Students will also learn how to write an applied research proposal, including data collection and analysis. Prerequisite(s): No prerequisites are required for this course. course outline	3.0
*COMP 9190 - Application Area Directed Studies can be a substitute for any of the courses: COMP 9130, COMP 9150, or COMP 9170.

Level 2 (15 weeks – January to April)			Credits
	COMP 9040	Human-centered Computing This course will introduce basic concepts related to software design as it relates to human computer interaction and social contexts in which software is used. Students will explore a brief history and foundational concepts in computing, software and algorithm design, and human computer interaction. In addition, through readings, case studies, and project work, students will learn to incorporate non-technical considerations in computing, such as social structures and ethical and other issues (e.g., social inequalities) that impact use, when designing software systems. Specifically, this will include considering the impact of software systems on individual and collective consciousness, designing to maximize agency of users, consciously avoiding amplifying social inequalities, considering environmental impacts, and taking into account the impact of values embedded in software design especially across different cultures. A secondary aim is to learn how to consciously effect constructive change through software systems. Prerequisite(s): No prerequisites are required for this course. course outline	3.0
	COMP 9080	Research Proposal This mandatory seminar will be taken at the end of term two, once students have an idea of what they will be working on during the project/thesis phase of this graduate program. The primary goal is to prepare students to focus on an applied research problem and publish or present their results. The seminar will include a workshop component in which the student begins to plan for their own project proposal by developing a preliminary document, to be presented to the instructor and peers for immediate feedback. Following the seminar, students will work to develop a formal proposal for their independent industry or applied research project, to be reviewed by the supervisory committee. Prerequisite(s): No prerequisites are required for this course. course outline
	COMP 9130	Applied Artificial Intelligence* This course introduces student to concepts, topics, issues, and methodologies related to Artificial Intelligence. Students will develop the skills required to evaluate, design, develop and improve Artificial Intelligence (AI) algorithms through hands-on projects and problem solving. Participants are expected to develop a portfolio of Al projects during this course. Prerequisite(s): No prerequisites are required for this course. course outline	3.0
	COMP 9150	Cyber Security for Applied Computing* This course introduces student to concepts, topics, issues, and methodologies related to Artificial Intelligence. Students will develop the skills required to evaluate, design, develop and improve Artificial Intelligence (AI) algorithms through hands-on projects and problem solving. Participants are expected to develop a portfolio of Al projects during this course. Prerequisite(s): No prerequisites are required for this course. course outline	3.0
*COMP 9190 - Application Area Directed Studies can be a substitute for any of the courses: COMP 9130, COMP 9150, or COMP 9170.

Levels 3 & 4			Credits
Thesis Path (30 weeks – September to April)
	COMP 9600	M.Sc. Thesis Students must submit a thesis as partial fulfillment of the Master of Science degree program requirements. The thesis should be based on original investigation and must demonstrate scholarship and critical judgement, as well as familiarity with methods of research and relevant literature in the chosen computing and/or application domain topics. The thesis should be at a high level of originality and examine a problem in depth. Elements of the thesis that are considered to constitute original scholarship and an advancement of knowledge must be clearly indicated. Prerequisite(s): 60% in COMP 9040 and 60% in COMP 9060 and S in COMP 9080 and 60% in COMP 9130 and 60% in COMP 9150 and 60% in COMP 9170 and 60% in COMP 9200 COMP 9190: Application Area Directed Studies 3.0 can be a substitute for any of the courses: COMP 9170, COMP 9130, or COMP 9150 course outline	12.0
	or
Project & Internship Path Students may take their industry internship in the Spring/Summer or Fall term and complete their research project in the following Fall or Winter term. Please note that COMP 9290 is offered in the fall term.
	COMP 9290	Special Topics in Applied Computing This interdisciplinary course provides an in-depth study of a selected topic in Applied Computing. The goal of the course is to develop students' ability to apply their knowledge of computational problem solving to an area of practical application. Students will learn how to analyze not only the computational aspects of the target application, but they will also learn how the social and scientific context of the problem impacts a suitable computational model and solution. Topics will vary from term to term, and may include applications of AI/ML, Data Analytics, Computational Simulation, and/or Software Engineering. While the emphasis is on Applied Computing, the students will also learn how to communicate computational solutions effectively to domain experts and stake holders. Prerequisite(s): Enrolment in the MSc program in Applied Computing, or permission of the instructor. course outline	3.0
	COMP 9400	Industry Internship Students in this course will work full time for one term in an external organization, or a BCIT research lab. The precise nature and scope of the work will vary. But the student will be required to be embedded in a workplace, where they will demonstrate their ability to contribute to a team that is solving applied computing problems. The student will maintain contact with their BCIT supervisor through weekly communication. Over the course of the internship, the student will also refine or develop a research proposal for the research project course (COMP 9500). Detailed procedures for the internship, including approval requirements and process, can be found in the Program Handbook. Prerequisite(s): 60% in COMP 9040 and 60% in COMP 9060 and S in COMP 9080 and 60% in COMP 9130 and 60% in COMP 9150 and 60% in COMP 9170 and 60% in COMP 9200 COMP 9190: Application Area Directed Studies 3.0 can be a substitute for any of the courses: COMP 9170, COMP 9130, or COMP 9150. and Program Approval course outline	6.0
	COMP 9500	M.Sc. Research Project Students must submit a project report as partial fulfillment of the Master of Science degree program requirements. Their project should be based on an industry problem, which was developed over the course of the COMP 9400 internship. The project must demonstrate critical thinking, familiarity with computing research methods, and familiarity with the domain of application. The project should exhibit originality and examine an industry problem to develop a full solution. The project does not need to be fully innovative, it can provide a new solution to a previously solved problem; however, it must include innovative aspects as compared to existing solutions, and these aspects need to be highlighted. Prerequisite(s): S in COMP 9400 course outline	3.0

Total Credits:			30.0

Transfer credit

Do you have credits from another BC/Yukon post-secondary school? Do you want to know if they transfer to courses here at BCIT? Check out BCIT's Transfer Equivalency Database to find out.

Program Details

This degree focuses on Applied Computing, which is fundamentally related to applying computing technology and computational methods to derive solutions to complex practical problems. Course work will emphasize current issues in industry, case studies, and applied research projects.

This program offers you a chance to work with an interdisciplinary and diverse team of academic supervisors that may include faculty from Computing, faculty from an application domain, as well as industry practitioners. You’ll also have the opportunity to undertake directed studies with a supervisor in a different department to explore a specific application area. For more information about faculty, visit the Faculty, Advisors & Staff page.

Applied research is fundamental to the program. Two paths are offered, diverging in second year:

Thesis Path – Path 1: complete a thesis project and defend it in your second year. You’ll need to demonstrate originality in the application of your knowledge, either through new publishable research, or a novel solution to an existing practical problem. This is the best path if you’re interested in possibly pursuing a future Ph.D.
Project & Internship Path – Path 2: a one-semester research project with a one-semester internship. The internship will embed you in a company where you can learn how advanced computing techniques are applied to solve interdisciplinary problems. The project may be done in collaboration with the industry sponsor from the internship, providing added value in terms of practical utility. Students will also complete a 3-credit special topics course, covering emerging areas in Applied Computing, such as Cloud Computing, Generative AI, or Deep Learning.

Both paths will require students to:

examine literature in a related discipline,
recognize gaps and limitations in existing technologies and processes,
organize and plan their approach, and
demonstrate competence in applying advanced techniques to solve problems.

In both paths, students will present a written argument that addresses a complex problem in applied computing.

The infographic shows an overview of the two path options: Thesis versus 2. Project & Internship

Program length

Two years, full-time.

Grading

Students will be required to maintain a minimum average of 70% across all courses in the program before starting their thesis or research project.

Student progress through the program will be monitored by the supervisor, in consultation with the Program Head.

Program delivery

In person: This program is delivered on campus.

Program location

Burnaby Campus
3700 Willingdon Avenue
Burnaby, BC

Graduating & Jobs

Job opportunities

Our grads will be able to lead and be part of exciting and essential technical transformations across organizations as our society and economy evolve through technology.

Technology in the workforce

The World Economic Forum (WEF) Future of Jobs 2023 predicts that technology adoption will remain a key driver of business transformation, especially in the areas of big data analytics, cloud computing, digitization of commerce and trade, AI, climate change and environmental management technologies, encryption and cybersecurity, agriculture technologies, digital platforms and apps.

WEF also reports that the fastest-growing roles relative to their size today are driven by technology, digitalization and sustainability.

The majority of the fastest-growing roles are technology-related roles. AI and Machine Learning Specialists top the list, followed by Sustainability Specialists, Business Intelligence Analysts and Information Security Analysts.

AI is rapidly becoming a catalyst for growth, driving new tech talent hiring. (CBRE 2024)

Local Tech Scene

Vancouver is one of the top three cluster cities for tech talent in Canada, with a tech talent workforce representing approximately 7.4% of the market. Toronto, Vancouver, and Montreal are the leading AI-development markets in Canada, accounting for 60% of the country’s AI-specialty tech jobs. (CBRE 2024)

Apply for graduation

Upon successful completion of all program requirements, complete an Application for BCIT Credential [PDF] and submit it to Student Information and Enrolment Services.

Allow approximately six to eight weeks for processing.

All financial obligations to the Institute must be met prior to issuance of any credential.

Faculty, Advisors & Staff

Erdem Gulova
Program Coordinator
Email: CompMSc@bcit.ca

Computing faculty

	Dr. Aaron Hunter Mastercard Chair in Digital Trust Academic Background Ph.D., Computing Science Research Activities Artificial Intelligence, Knowledge Representation, Trust, Information Security Relevant Links Bio
	Dr. Michal Aibin Academic Background Ph.D., Informatics Research Activities Networking, cloud computing, UAV/RPAS/drones, computer vision, autonomous vehicles, AI, machine learning Relevant Links Personal website \| Google Scholar \| LinkedIn
	Dr. Borna Noureddin Academic Background Ph.D., Biomedical Engineering Research Activities Social implications of technology, human-computer interaction, assistive technologies, biomedical engineering
	Dr. Mirela Gutica Academic Background Ph.D., Curriculum Studies (Educational Technology) Research Activities Advanced learning technologies and intelligent tutoring systems; computer science education research; cognition, emotion, motivation and learning; HCI and adaptive interfaces Relevant Links Bio \| BCIT Researchers \| ACM
	Dr. Chi En Huang Academic Background Ph.D., Electrical & Computer Engineering Research Activities Computer Architecture, Wireless Communication Systems, Artificial Intelligence, Machine Learning, Optimization

Affiliated faculty outside Computing

The following BCIT faculty may be suitable supervisors or co-supervisors for relevant applications of computing.

	Dr. Jaimie Borisoff Director, MAKE +, BCIT Applied Research Academic Background Ph.D., Neuroscience, Bachelor of Applied Science in Engineering Physics Research Interests Quantitative and qualitative evaluation of people using technology (e.g., eye tracking when using a wheelchair and Mocap), development of new devices in rehabilitation, medical devices, wheeled mobility, assistive technology, adapted exercise and fitness, accessibility, rehab robotics Relevant Links MAKE + Product Development \| Rehabilitation Engineering Design Lab \| ICORD
	Dr. Michael Harder Academic Background Ph.D., Physics Research Interests Condensed matter physics focused on magnetism and spin dynamics. In particular: spintronics, magnetic materials, magnetization dynamics, spin-photon hybridization, collective/emergent phenomena and related applications. Relevant Links Google Scholar
	Dr. Dean Hildebrand Academic Background Ph.D., Biochemistry and Molecular Biology Research Interests DNA Analysis
	Dr. David Holloway Academic Background Ph.D., Physical Chemistry Research Interests Developing, coding and testing mathematical models in biology; coding; optimization of equation solution and parameter fitting; machine learning for solution sets; discrete vs. continuous representations of gene networks; image analysis; mathematical models of animal and plant development Relevant Links Personal website
	Dr. Yvette Jones Academic Background Ph.D., Biomedical Engineering Expertise Quantitative and qualitative evaluation and validation of technology, including biomechanics, human factors, ergonomics, and medical device development Relevant Links MAKE + Team
	Dr. Djamel Khelifi Academic Background Ph.D., Organic Chemistry Research Interests Pharmaceuticals, Organic Synthesis and Biosynthesis of Natural Products, Analytical Chemistry, natural health products, Anti-Cancer Polyacetylenes
	Dr. Stefan Lukits Academic Background Ph.D., Philosophy Research Interests Information theory, formal epistemology, probability theory Relevant Links Publications
	Dr. Moein Manbachi Academic Background Ph.D., Engineering Science Research Interests Smart grid optimization using AI, digital twin modeling of critical energy infrastructure, data/energy hub design, smart grid energy management system, energy infrastructure cybersecurity Relevant Links SMART Team \| Cybersecurity Lab \| Google Scholar
	Dr. Sarah McLeod Academic Background Ph.D., Microbiology and Immunology Research Interests Microbiology, immunology
	Dr. Jennie Moore Academic Background Ph.D., City/Urban, Community and Regional Planning Research Interests Measuring and managing for living within earth’s carrying capacity at the city scale; Integrated energy and materials flows analysis; Eco-footprint impacts; Greenhouse gas management; Municipal strategies for climate action and resilience Relevant Links Centre for Ecocities
	Dr. Rodrigo Mora Academic Background Ph.D., Building Information Modelling, P. Eng. Research Interests Building science: smart buildings; occupant-centric design and operation; building environmental quality; climate change and the built environment; machine learning applications; remote sensing and monitoring Relevant Links Bio
	Dr. Takashi Nakamura Academic Background Ph.D., Physics Research Interests Quantum mechanics, machine learning, simulation, quantum computing, quantum communication
	Dr. Barry Pointon Academic Background Ph.D., Physics Research Interests Medical imaging, nuclear medicine, particle physics, machine learning, data analysis, simulation
	Dr. Eric Saczuk Academic Background Ph.D., Factors Affecting Risk from Natural Hazards Research Interests GIS, geomorphology, remote sensing, remotely piloted aircraft systems, mapping sciences Relevant Links RPAS Hub \| Indro Robotics
	Dr. Vidya Vankayala Director, SMART Academic Background Ph.D., Electrical & Computer Engineering Research Interests Smart grids, monitor and manage power system assets, cyber-physical system consequence modeling to prevent attacks on electrical networks
	Dr. Steve Walker Academic Background Ph.D., Chemistry – Molecular reaction photo-dynamics Research Interests -Computational chemistry, focused on how can we leverage machine learning to become more efficient in the use of computational resources involved in theoretical chemical systems.-Trying to bridge between conventional computational chemistry such as density functional theory and couple cluster systems with the advances in machine learning and AI.-Novel mass spectrometry techniques such as differential ion mobility.-Molecular clusters. Relevant Links Google Scholar
	Dr. Carol Wenzel Academic Background Ph.D., Plant Sciences Research Interests Biotechnology, plant developmental biology, hormone physiology, vascular patterning, leaf production, drought stress tolerance, exercise/rehabilitation

Advisory committee

BCIT is well-respected by employers for its ties to industry. In Computing, this connection is formalized through a Program Advisory Committee (PAC) comprised of experts in a range of roles from a cross-section of companies. The department consults regularly to ensure program currency and relevance.

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