- People
- Leadership & Staff
- Research faculty
- Gabriela Aceves-Sepúlveda
- Alissa N. Antle
- Sheelagh Carpendale
- Parmit Chilana
- Jon Corbett
- Steve DiPaola
- Halil Erhan
- Brian Fisher
- Diane Gromala
- Marek Hatala
- Kate Hennessy
- Alireza Karduni
- Sylvain Moreno
- Carman Neustaedter
- Will Odom
- Philippe Pasquier
- Niranjan Rajah
- Bernhard Riecke
- Gillian Russell
- Thecla Schiphorst
- Chris Shaw
- Wolfgang Stuerzlinger
- Ron Wakkary
- Ö. Nilay Yalçin
- Teaching faculty
- Emeritus
- Adjunct Faculty
- Alumni
- Work at SIAT
- Research
- Programs
- News & Events
- Spaces & Equipment
- StudioSIAT
- Media
- Showcase
- Showcase Submission Form
- Fall 2024 Project Showcase
- Summer 2024 Project Showcase
- Spring 2024 Project Showcase
- Fall 2023 Project Showcase
- Spring 2023 Project Showcase
- Fall 2022 Project Showcase
- Spring 2022 Project Showcase
- Fall 2021 Project Showcase
- Spring 2021 Project Showcase
- Fall 2020 Project Showcase
- Contact
- Staff & faculty resources
Human Centred-Artificial Intelligence
The Human-Centred Artificial Intelligence (AI) micro-certificate is a suite of four SFU 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 self-assessments to see if you are sufficiently comfortable with the necessary programming concepts.
Introducation to Visual Analytics
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 Data & Dialogue Lab’s website.
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 head to SFU’s Lifelong Learning page for IAT-355N.
Current SFU students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
Exploring Artificial Intelligence: Its Use, Concepts, and Impact
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 head to SFU’s Lifelong Learning page for IAT-360N.
Current SFU students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
Generative AI and Computational Creativity
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 head to SFU’s Lifelong Learning page for IAT-460N.
Current SFU students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
Data Science for Human-Centred Systems
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 head to SFU’s Lifelong Learning page for IAT-461N.
Current SFU 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 SFU Lifelong Learning and links to sign-up for each course are available below. Current SFU students are unable to sign-up for these courses through Lifelong Learning, and must register for the courses through GoSFU.
- Introduction to Visual Analytics (IAT-355N) sign-up
- Exploring Artificial Intelligence: Its Use, Concepts, and Impact (IAT-360N) sign-up
- Generative AI and Computational Creativity (IAT-460N) sign-up
- Data Science for Human-Centred Systems (IAT-461N) sign-up
Current SFU 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’s 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’s work →
Marek Hatala
Dr. Marek Hatala’s 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’s work →
Ö. Nilay Yalçın
Dr. Nilay Yalçın’s 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 →
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’s work →
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.