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Human Centred-Artificial Intelligence
The Human-Centred Artificial Intelligence (AI) micro-certificate is a suite of four 51社区黑料courses developed with guidance from industry intended for alumni or professionals working in the industry to gain working knowledge with AI. Learners can apply to all or any of the courses, though all four would need to be completed to receive the Human-Centred AI micro-certificate.
Further down this page we detail:
There are four courses that form the micro-credential. You can complete one and receive a digital badge or complete all four to receive the Human-Centred AI micro-certificate.
All four courses require some programming knowledge to be successful. If you are unsure if you are prepared for the course please head our to see if you are sufficiently comfortable with the necessary programming concepts.
This course focuses on the design and implementation of interactive computer visualization techniques for the analysis, comprehension, and explanation of large collections of abstract information. The application of principles from perception, information visualization, interaction and visual analytics will be covered. Introduces tools for programming geometric information and displaying the results.
Learners in this course will:
- Gain an understanding of visual analytics principles and apply those principles to creating effective visualizations.
- Work with HTML, CSS and JavaScript to build effective visualizations and explanations of data insights.
- Learn D3.js and Vega-lite to assist in creating custom interactive visualizaitons.
More information on what this course involves is available at the .
Course offering:
This course will be offered remotely (online) in the Fall 2025 semester; from early September to early December (2025).
Sign-up:
To sign-up for this course .
Current 51社区黑料students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
A course designed to provide a comprehensive and accessible introduction to the world of artificial intelligence that will empower the learners to navigate the AI-driven future. Learners will explore fundamental AI concepts, including machine learning, neural networks, natural language processing, and computer vision; discover real-world applications, ethical considerations, and the societal impact of AI.
Learners in this course will:
- Learn about key AI concepts and building a familiarity with AI Tools and software (such as TensorFlow, scikit-learn, and PyTorch).
- Apply and evaluate how AI can be embedded in daily activities.
- Explore ethical frameworks and real-world case studies on the impact of AI.
Course offering:
This course will be offered blended (a mix of in-person and online) in the Fall 2025 semester; from early September to early December (2025).
Sign-up:
To sign-up for this course .
Current 51社区黑料students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
An in-depth introduction to the design and use of generative systems in the context of creative practices. This course surveys the families of algorithms and interfaces used in generative artificial intelligence (Al) and computational creativity, to augment or automate creative tasks across domains.
Learners in this course will:
- Prototype and test generative models in Python/PyTorch on Google Collab, including integrating LLMs in your projects.
- Use cloud-based computing for genAI using RunDiffusion.
- Develop their own workflows with diffusion models in ComfyUI.
- Become proficient in using the Autolume neural visual synthesizer (small data and model crafting with StyleGan2-ADA).
As AI is a fast evolving space the list above may change or adjust to stay as up-to-date as possible.
Course offering:
This course will be offered remotely (online) in the Spring 2026 semester; from early January to mid-April (2026).
Sign-up:
To sign-up for this course .
Current 51社区黑料students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
The course covers the data science processing pipeline, from understanding the goals and questions of a project to presenting results effectively using data visualizations. You will learn feature engineering, model building and interpretation, including regression, classification, clustering, decision trees, random forests, and support vector machines. A practically oriented project is also included where you will apply what you've learned with widely used Python libraries for data analysis.
Learners in this course will:
- Work through the data analytics process from beginning to end.
- Identify techniques used in each step of the analytics process.
- Learn the steps of data cleaning, feature engineering, analytical technique selection, and results interpretation.
- Make use of Python to carry out the data analysis.
Course offering:
This course will be offered remotely (online) in the Summer 2026 semester; from early May to early August (2026).
Sign-up:
To sign-up for this course .
Current 51社区黑料students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
How to sign up for the courses
Signing up for any of the micro-credential courses is managed by 51社区黑料Lifelong Learning and links to sign-up for each course are available below. Current 51社区黑料students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
Current 51社区黑料students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
Alireza Karduni
Dr. Alireza Karduni鈥檚 work focuses on designing interactive visual tools that help people understand and make decisions based on new information. Recognizing the socially and politically situated nature of information ecosystems, he researches how our existing views might influence our receptivity to new (mis)information and how such dynamics might influence our interactions in virtual and physical spaces.
Read more about Alireza鈥檚 work 鈫�
Marek Hatala
Dr. Marek Hatala鈥檚 research is driven by the problems arising between the computing systems and their users. The areas of his prior interests include configuration engineering design, organizational learning, semantic interoperability, ontologies and semantic web, user modeling in ubiquitous and ambient intelligence environments, and software engineering and service oriented architectures.
Read more about Marek鈥檚 work 鈫�
脰. Nilay Yal莽谋n
Dr. Nilay Yal莽谋n鈥檚 is an artificial intelligence (AI) researcher with an interdisciplinary background in Cognitive Science and Engineering. Her research focuses on modeling socio-emotional behaviours in computational systems in order to develop interactive systems that can understand human behaviour and advance our understanding of human cognition by providing us means to evaluate our assumptions in a systematic and controlled environment. She has been focusing on complex concepts such as empathy, affect, personality and theory of mind in a variety of contexts such as healthcare, education and creativity.
Read more about Nilay's work 鈫�
Philippe Pasquier
Dr. Philippe Pasquier leads a research-creation program around generative systems for creative tasks. As such, he is a scientist specialized in artificial intelligence, a software designer, a multidisciplinary media artist, an educator, and a community builder. Pursuing a multidisciplinary research-creation program, his contributions bridge fundamental research on generative systems, machine learning, affective computing and computer-assisted creativity, applied research in the creative software industry, and artistic practice in interactive and generative art.
Read more about Philippe鈥檚 work 鈫�
Frequently Asked Questions
What are the prerequisites for these courses?
There are no micro-credential prerequisites, but each course has self-assessment tests which learners are encouraged to ensure they are prepared for the courses. You can find the self-assessments here: .
How many people will be in the class?
Class sizes typically range from 24 to 72 students, depending on the course. Each class includes both undergraduate students working toward their SIAT degrees and non-credit learners in the micro-certificate program.
As a micro-certificate student, you鈥檒l be learning alongside university students engaged in cutting-edge design and technology education. This creates a unique opportunity to experience an academic environment, gain insights from peers with diverse perspectives, and build your skills in a collaborative, university-level setting.
Who should take these courses?
The Human-Centred AI micro-credential is designed for a wide range of learners who want to understand and apply AI through a human-first lens. You should consider these courses if you are:
- A creative technology professional looking to integrate AI into your design, media, or interactive work
- A designer, artist, or developer interested in how generative AI, visual analytics, and human鈥揂I collaboration can enhance your practice
- A recent graduate or student from programs in design, computing science, data science, or interactive arts and technology who wants to develop industry-relevant, portfolio-ready AI skills
- A working professional seeking upskilling or reskilling in ethical, inclusive, and practical uses of AI tools and platforms
- An international learner who meets the programming prerequisites and wants to build cutting-edge experience through online or hybrid short-term study
No matter your background, if you're curious about AI's creative and human dimensions, and you have some programming experience, these courses are for you.
Who are the instructors?
The micro-credentials are taught by 51社区黑料faculty members who are experts in their fields:
Alireza Karduni: Dr. Alireza Karduni鈥檚 work focuses on designing interactive visual tools that help people understand and make decisions based on new information. Recognizing the socially and politically situated nature of information ecosystems, he researches how our existing views might influence our receptivity to new (mis)information and how such dynamics might influence our interactions in virtual and physical spaces.
Marek Hatala: Dr. Marek Hatala鈥檚 research is driven by the problems arising between the computing systems and their users. The areas of his prior interests include configuration engineering design, organizational learning, semantic interoperability, ontologies and semantic web, user modeling in ubiquitous and ambient intelligence environments, and software engineering and service oriented architectures.
脰. Nilay Yal莽谋n: Dr. Nilay Yal莽谋n鈥檚 is an artificial intelligence (AI) researcher with an interdisciplinary background in Cognitive Science and Engineering. Her research focuses on modeling socio-emotional behaviours in computational systems in order to develop interactive systems that can understand human behaviour and advance our understanding of human cognition by providing us means to evaluate our assumptions in a systematic and controlled environment. She has been focusing on complex concepts such as empathy, affect, personality and theory of mind in a variety of contexts such as healthcare, education and creativity.
Philippe Pasquier: Dr. Philippe Pasquier leads a research-creation program around generative systems for creative tasks. As such, he is a scientist specialized in artificial intelligence, a software designer, a multidisciplinary media artist, an educator, and a community builder. Pursuing a multidisciplinary research-creation program, his contributions bridge fundamental research on generative systems, machine learning, affective computing and computer-assisted creativity, applied research in the creative software industry, and artistic practice in interactive and generative art.
When are each of the courses offered?
- IAT鈥�355: Fall鈥�2025, Sept 8-December 1, 2025 (asynchronous, online)
- IAT鈥�360: Fall鈥�2025, Sept 3-November 26, 2025 (hybrid: in鈥憄erson + synchronous online),
- IAT鈥�460: Spring鈥�2026, Jan 5 鈥� April 25, 2026 (asynchronous, online)
- IAT鈥�461: Summer鈥�2026, May 11-August 10, 2026 (asynchronous, online)
Will I receive transcripts or credit when completing non鈥慶redit micro鈥慶redentials?
Learners will receive a digital badge upon completing each micro-credential.
Learners are also able to get an official transcript through 51社区黑料Lifelong Learning.
Can these badges or courses count toward a SIAT degree?
Yes. If you later apply and are admitted to an 51社区黑料SIAT undergraduate degree, these micro鈥慶redentials can be applied toward degree requirements.
How do I sign up, and who can register?
Micro-credential learners can register for each course through SFU鈥檚 Lifelong Learning portal.
Current 51社区黑料students use Go51社区黑料instead.
I鈥檓 a current 51社区黑料student. Can I take these courses?
Current 51社区黑料students completing a degree can register for these courses during SFU鈥檚 regular enrolment period through go.sfu.ca.
Micro-certificate course seats are reserved for non-credit learners.
How do these courses connect with industry?
Courses are developed in collaboration with the SIAT Human-Centred Industry Advisory Board, DigiBC and SIAT faculty working in applied research and industry contexts.
Can international students take SIAT鈥檚 micro-credentials without a study permit?
International students do not need a study permit if they are registering in the following online courses: IAT 335N, IAT 460N, IAT 461N.
Online courses do not require a study permit if you are studying from outside Canada.
Students wishing to register in IAT 360N, which is a blended course requiring in-person and online attendance, will require a study permit as it contributes to the SIAT Human-Centred AI micro-certificate, which takes more than 6 months in duration to complete.
Can I study from outside of Canada?
Studying remotely (online) from outside Canada does not require a study permit or visa.
What type of visa or permit do I need to come to Canada for a short in-person course?
Check what you need:
Will I receive a letter of acceptance for visa purposes?
SIAT/51社区黑料may issue documentation confirming your enrollment in the non-credit program, but non-credit courses do not typically issue a formal 鈥淟etter of Acceptance鈥� like for-credit programs. If you require a Letter of Acceptance, please follow up with us to discuss more, 蝉颈补迟鈥慼肠补鈥憄谤辞驳谤补尘蔼蝉蹿耻.肠补 .
Can I extend my stay in Canada if I want to take more courses after completing the micro-certificate?
Not automatically. If you enter Canada as a visitor, your authorized stay is typically up to 6 months. If you later decide to take a longer program, you will likely need to apply for a study permit and meet different eligibility criteria.
Where can I find the most up-to-date information on study and visa requirements?
Always refer to official sources:
- IRCC: Study in Canada
- IRCC:
- IRCC:
Who can I contact for international student support at SFU?
The International Services for Students (ISS) office at 51社区黑料provides immigration and visa guidance: or phone (778-782-4232)
How can I get a refund?
See refund details here: /continuing-studies/student-info/policies.html
How can I get help or ask questions?
Contact 蝉颈补迟鈥慼肠补鈥憄谤辞驳谤补尘蔼蝉蹿耻.肠补 if you have any further questions.
Have questions about the micro-credential?
If you have questions about the Human Centred AI micro-credential that are not answered about the above please feel free to reach out to siat-hca-program@sfu.ca and we will get back to you as promptly as possible.