deploying AI

Apr 01 2026

DSI Industry Partner AstraZeneca Canada builds opportunities for exchange with emerging talent in data science and AI

The ongoing partnership between the Data Sciences Institute and AstraZeneca Canada enables a dialogue between one of the country’s leading research-based pharmaceutical companies and emerging talent at one of the world’s leading universities in data science and AI.

Access to emerging data science and AI talent is part of what brought AstraZeneca Canada to DSI as an Industry Partner. Investing in this talent pipeline is part of their strategy to create global impact by using data to transform science and deliver life-changing medicines.

The Data Science and AI Talent Showcase this January was an opportunity for AstraZeneca to hear from DSI scholars trained in data sciences, and AI methods and tools that align the pharmaceutical sector’s needs. The poster session showcased applied research from undergraduate and doctoral students, and postdoctoral fellows from across the U of T and research institute partners who were keen for the opportunity to speak with and gain insight from representatives from AstraZeneca Canada.

The Industry Speaker Series forum on April 27 is the next turn in the dialogue. This interactive afternoon will feature three speakers from AstraZeneca Canada offering insights from different perspectives within the organization: Martin Booth, Head of Analytics & Data Excellence, Devon Prontack, Senior Manager, Data Science & Innovation, and Amyn Sayani, Head of Medical Evidence.

AstraZeneca uses real-world health data to generate insights, address evidence gaps, and navigate challenges in accessing and connecting health data across Canada. Their speakers will share perspectives on medical evidence, synthetic data, and decision making in applied commercial data science. By highlighting elements of their work and challenges that they face, AstraZeneca opens avenues for discussion and collaboration with DSI’s community.

The entire afternoon is designed to enable such collaboration and dialogue. With ample open networking providing opportunities for unstructured dialogue, AstraZeneca will also join Michael Brudno (Chief Data Scientist, University Health Network), Laura Rosella (Professor, Dalla Lana School of Public Health, University of Toronto), Lillian Sung (Chief Clinical Data Scientist, The Hospital for Sick Children) and Mina Tadrous (Associate Professor, Leslie Dan Faculty of Pharmacy, University of Toronto) for a panel moderated by Lisa Strug, Director of the Data Sciences Institute. Drawn from U of T and affiliated hospital partners, these experts will bring insights on implementation challenges, data access realities, and opportunities for collaboration between industry and the research community.

Lisa Strug, Director, Data Sciences Institute, speaks to the ongoing value of this partnership. “We see this as truly a two-way collaboration. We are thrilled to see the connections that are formed through AstraZeneca’s access to the U of T talent pipeline and the DSI community’s exposure to AstraZeneca’s insights in practice.”

“We’re excited to join the Data Sciences Institute to discuss how industry is using health data to generate real-world evidence and where collaboration can help unlock data science insights for healthcare,” says Martin Booth, Head of Analytics & Data Excellence at AstraZeneca Canada.

The Data Sciences Institute welcomes industry leaders ready to launch their own dialogue with the DSI community. Our Industry Partnership model connects industry leaders with top-tier data science, fostering collaboration through industry engagement and trainee development opportunities. Organizations gain direct access to exceptional students and researchers, strengthening their presence in the next generation of data-driven talent. See our Industry Partnership Model and contact parterships.dsi@utoronto.ca to get started.

Mar 25 2026

Data science in finance is revolutionizing the industry

How University of Toronto’s Data Sciences Institute is helping to develop tomorrow’s professionals

By Ursula Leonowicz

In Michelle Liu’s line of work at the intersection of digital data and design, there’s a constant need for learning and upskilling; not just for the sake of technological advancement but because of the productivity and growth associated with it.

“Fundamentally, especially over the past few years with the popularity of ChatGPT and now, OpenClaw, everyone is thinking about how we’re using AI tools, which is changing how we work but also what we work on,” says Liu, director of credit analytics at Home Equity Bank.

“How we work is fairly easy to understand, but there’s also a deeper discussion going on that’s focused on what we should be working on as professionals, and I think it’s really about understanding our value,” she says. “In the financial sector, we deal with vast amounts of legal files that need to be reviewed, but it’s extremely time-consuming and not the best use of time, in my opinion.”

Which is where data science becomes a game changer.

The practice of collecting and preparing data, performing feature engineering, selecting and training models, and evaluating their performance and understanding the uncertainty associated with them, data science is fast becoming a key tool transforming the financial sector.

Designed to support professionals looking to deepen their knowledge in the growing field of data science, the University of Toronto’s Data Sciences Institute (DSI) oﬀers a suite of AI, machine learning and data science microcredentials, which were launched with the financial support of the Government of Canada.

Established in 2021, the Data Sciences Institute was created to unify data sciences research and training across the university, its affiliated research institutes and external partners.

Since then, the university has leveraged its leadership and expertise in data sciences and AI to facilitate collaboration, as well as the development and application of new data science methodologies and tools in a training-focused environment.

Helping professionals build practical data and AI capabilities that align with evolving workplace needs, the DSI offers three stackable microcredentials — Data Science Foundations, Machine Learning Foundations and Deploying AI — to help employers upskill existing staff, including in the financial sector.

“Providing opportunities for upskilling and promoting from within is one of the best ways for employers to encourage employee retention, and transform their learning into productivity and growth,” says Liu, who previously completed a DSI certificate.

“For me, pursuing a DSI certificate gave me the confidence to manage my team knowing what each one of them deals with on the technical front. It was a rewarding experience to push myself.”

Microcredentials for the real world

Created to help learners develop skills aligned with current industry and research practices, Data Science Foundations builds proficiency in the Unix shell, Git and GitHub, Python and SQL. Using practical examples and focused on how to get value from AI, Deploying AI enables learners to develop practical skills for deploying and operating AI systems in real-world environments.

In Machine Learning Foundations, professionals develop practical skills aligned with current industry practices for building, evaluating and deploying machine learning systems.

As part of each DSI microcredential, participants attend live online sessions for about 7 hours per week including support, over three to eight weeks, depending on the microcredential. These sessions have assignments and assessments designed to create opportunities to apply newly learned skills. DSI provides flexibility so that learners can take individual microcredentials to strengthen specific competencies or combine them toward a full certificate. 

Shaped by industry input and overseen by University of Toronto faculty, the microcredentials emphasize hands-on, applied learning to ensure relevance across a wide range of roles and sectors. The goal is to enable learners and organizations to strengthen internal capability, support role evolution and integrate data and AI more eﬀectively as part of broader workforce transformation.

The University of Toronto was in the global top 10 for the 2025 QS World University Rankings for Data Science and AI, which is a reflection of its leadership and expertise. Providing flexible, quality pathways for workforce transformation, the DSI is a hub and incubator for data science research, training and partnerships.

To register for a microcredential, or for more information about how to make the microcredentials offered by the U of T’s Data Sciences Institute available to employees, visit certificates.datasciences.utoronto.ca.

This story was created by Content Works, Postmedia’s commercial content division, on behalf of the University of Toronto.

Jan 13 2026

U of T staff: Level up your AI skills with the Data Sciences Institute!

University of Toronto staff who want to build the skills and confidence to apply generative AI effectively in their work have a new opportunity for learning with the Data Sciences Institute.

With AI becoming increasingly important for work, the University’s AI Task Force’s report, Toward an AI-Ready University, calls for AI literacy and training for all employees.

Deploying AI offers a unique value as it is short, targeted learning experience dedicated to the frameworks, tools, and applied skills that professionals need to navigate the operational and organizational challenges of AI integration. The microcredential emphasizes real-world applications and toolsets, enabling learners to contribute to AI integration initiatives in their workplaces. Participants gain in-demand expertise in model evaluation, prompt engineering, and navigating deployment frameworks.

DSI is a hub for learning data science and AI and has offered not-for-credit data science, machine learning and AI certificates and microcredentials for several years for professionals outside U of T. DSI also offers certificates for doctoral students in collaboration with the School of Graduate Studies, and the Machine Learning Bootcamp for Faculty members offered with the Centre for Analytics and Artificial Intelligence Engineering (CARTE).

U of T staff can now also register for DSI’s microcredentials. Starting with Deploying AI, offerings will be searchable on the Centre for Learning, Leadership & Culture learning management system for U of T staff as they are scheduled throughout the year.

To celebrate this opportunity for U of T staff, we spoke to Philip Rudz, a aculty of Arts & Science staff member who completed Deploying AI in the fall.

Philip works in the Dean’s Office as a Service and Technology Delivery Lead, Teaching & Learning.

“A significant part of my role is evaluating new tools and technologies to stay current of what our instructors and administrative staff might be exposed to or request to use.”

Philip had experimented with Generative AI and various machine learning tools for several years. “I am part of the Arts & Science Dean’s Advisory Committee on AI,” he said, “And I have delivered several workshops to A&S admin staff about GenAI and also took part in developing the governance and data security guidelines as part of the AI Task Force that was convened in 2024-25.”

Still, Philip says he wanted exposure to a more formal instructional setting as opposed to self-learning. “The quality of instruction was excellent,” he says, “and the instructor and support staff were really outstanding.”

“I anticipated that the cohort would be more technical than me – which I thought would be valuable experience. I also wanted insight into what folks in the private sector were doing with AI implementation and was not disappointed as it was a large and diverse cohort. I really appreciated the expectation that students would be familiar with the basics of Python and that the instructor never slowed down the pace. I found the exercises challenging, but not overly so, and well designed to cater to a range of experience levels.”

Bill Brennan, Assistant Director, Learning and Leadership Development, Centre for Learning, Leadership & Culture in the Division of People Strategy, Equity & Culture, is enthusiastic about the inclusion of Deploying AI for U of T staff.

“For those looking to build on existing programming knowledge, the Deploying AI microcredential is an opportunity to gain hands-on, practical skills, to meet our needs to support AI literacy for U of T employees” he notes.

Registration is open for the February session of Deploying AI ! U of T staff may be eligible to apply for the Staff Tuition Waiver, depending on their employee group and how the learning relates to their role.

Nov 18 2025

Deploying AI Microcredential Sees Soaring Interest from Professionals

The Data Sciences Institute’s Deploying AI microcredential is a massive success in its first session. Organizations are seeking employees who can deploy AI responsibly and effectively—and professionals are responding with incredible demand for learning opportunities to build their skills.

Deploying AI is a hands-on opportunity to dive into the power of Large Language Models (LLMs). Learners develop the technical know-how and practical strategies needed to take AI from prototype to production.

Responding to input from learners and employers, DSI launched Deploying AI this fall and the enthusiasm from learners was palpable. The offering quickly sold out, reflecting soaring demand for the tools and confidence to deploy generative AI at scale.

The microcredential builds on the success of the DSI Data Science and Machine Learning Software Foundations Certificates offered with the financial support of Upskill Canada, powered by Palette Skills and the Government of Canada. For learners that have completed a Certificate, this microcredential is a next step in deepening their AI capabilities.

Deploying AI incorporates case studies from industry. Recently, learners heard from Sepehr Sisakht, an industry leader who is applying AI in practice as CEO of Shyftbase Inc. Learners gained a firsthand look at how AI deployment challenges are approached in a real-world setting. Applied perspectives like this bridge the gap between technical training and practical implementation, as learners gain insight into the workflows, trade-offs, and decisions faced by professionals deploying AI at scale.

“We developed Deploying AI in response to industry demand. Employers need people who can deploy and scale AI solutions in the real-world, now,” says Prof. Rohan Alexander, Director, Technical Skills and Curriculum (Faculty of Information and Department of Statistics, Faculty of Arts & Science).

“We’ve heard from our learners that our microcredential is making a real difference, whether they are preparing for that next great job or are in a role where they can put their learnings into practice right way. The response has been phenomenal.”

That response is echoed in the feedback on Deploying AI from learners. Learners highlighted the immediate usefulness of the microcredential, noting that the microcredential “provided a great primer to the tools and concepts for building AI solutions” and that the theory was useful and the practical knowledge immediately applicable to my work.”

Learners also emphasized the value of hands-on projects, noting that the assignments allowed them to showcase their ability and build credibility as AI professionals.

Registration is open for the February session of the Deploying AI microcredential. Don’t miss your chance to build the skills employers need to deploy AI effectively.

Sep 15 2025

Helping prepare Canada’s financial services workforce with AI literacy

How U of T’s Data Sciences Institute is helping professionals and employers stay competitive

As digital literacy becomes crucial to navigating the financial sector, the rapid pace of change can feel overwhelming for many mid-career experts and their employers, alike. This is particularly true in areas such as data sciences, artificial intelligence (AI) and machine learning.

Hiring professionals who are proactively adapting to the rise of data science and generative AI is one of the smartest ways businesses can stay competitive.

The University of Toronto’s Data Sciences Institute (DSI), a hub for data science research, training and partnerships, is helping businesses do just that by growing a pool of job-ready professionals. The DSI has upskilling certificates and microcredentials targeting the growing demand for professionals in finance and other fields to become knowledgeable in AI and understand how available tools can enhance their work.

Since launch, over 500 professionals have completed certificates, forming a job-ready talent pool aimed at bridging the gap between skilled candidates and employers. The DSI plays a vital role and is dedicated to creating new career paths for untapped talent to unleash their full potential.

As a manager of anti-money laundering and compliance data at Scotiabank, Matias Velastegui is one such professional. In search of a way to boost his technical skills, he completed Machine Learning Software Foundations, a 16-week intensive certificate at the DSI.

With the financial support of Upskill Canada, powered by Palette Skills and the Government of Canada, DSI certificates and microcredentials train mid-level professionals on digital literacy skills, including AI and machine learning, and are designed to meet the talent needs of high-growth sectors.

“It provided me with valuable tools that I’m confident I’ll apply in future professional and academic projects,” Velastegui says.

Certificates and microcredentials at the DSI are delivered live online, with weekly support through virtual office hours. Included are opportunities to learn from industry experts during case studies that provide participants with important insights into the professional world of data science and AI analytics.  In parallel to the technical training, learners have access to career transition support and exclusive employer networking events, which strengthens talent pipelines and helps keep Canadian businesses globally competitive.

While the certificate offers a comprehensive data science and machine learning overview, the DSI also offers a shorter, three-week microcredential on Deploying AI that focuses on building AI applications to augment work tasks. Deploying AI provides professionals with technical and strategic skills to turn AI prototypes into practical, workplace-ready solutions.

Velastegui says he decided to pursue the DSI certificate because it combined academic rigour with a practical focus. In his current role, he works extensively with SQL and Python languages. Through the DSI certificate, he learned new strategies for approaching complex queries, more efficient ways of handling data and best practices for data governance.

“From ensuring data integrity to grasping the mathematical principles of neural networks, professionals must be actively engaged in these advancements and prepared to evolve alongside them,” Velastegui says.

Now, he plans to hire other DSI upskilling participants to his own team. Velastegui is confident in the DSI’s focus on improving coding expertise and collaboration skills in virtual environments.

The DSI offers employers looking for new talent the opportunity to share job opportunities with its pool of participants, all of whom have post-secondary degrees and now have enhanced skills in data science and machine learning.

The certificates in Data Science and Machine Learning Software Foundations offer part-time coursework, so participants can continue working regular hours. Sakib Sadat, an intelligent automation program manager at Manulife, says the certificate is intensive but worth the time commitment.

Sadat says there has been a strong industry push for professionals to boost their skills using AI and machine learning tools, both for company standards and for personal development. Participating in the DSI’s certificate was a way for him to improve his productivity and the quality of his work.

Through the certificate, Sadat gained the ability to critically assess and identify which AI solutions presented by clients add real value in his current role.

“This certificate was one way to get the accumulated technical expertise to make those assessments on whether or not AI is going to actually be productive,” Sadat says.

Beyond the technical skills, Sadat and Velastegui agree that adding a University of Toronto AI-related certification to your resume is a good way to stand out in a pool of professionals, either when looking to move up internally or make a career switch.

“From a career progression standpoint, AI is a personal brand and selling feature in the industry, whether you’re in IT or not,” Sadat adds.

For professionals looking to learn more about the DSI’s upskilling offerings and employers accessing the DSI professional talent pool, visit certificates.datasciences.utoronto.ca.

This story was created by Content Works, Postmedia’s commercial content division, on behalf of the Data Sciences Institute.