AI bootcamp (Toronto) - Accelerate AI with Google Cloud

◎ Online

Hosted by Massachusetts Institute of Technology (MIT)

Build production-ready AI and machine learning solutions without writing a single line of code. This comprehensive 12-week online program from MIT Professional Education transforms aspiring data scientists and business professionals into AI practitioners through hands-on, no-code workflows. Starting November 27, 2026, you'll master the latest AI technologies—from supervised learning and neural networks to Generative AI and autonomous agents—using intuitive platforms that eliminate traditional coding barriers. What You'll Master This industry-aligned curriculum covers the complete AI development lifecycle across 10 core modules and additional self-paced content. You'll explore data science fundamentals, prediction methods using regression and neural networks, decision systems, recommendation engines, and computer vision techniques. Advanced modules dive deep into Generative AI foundations, prompt engineering, and Agentic AI—the cutting edge of autonomous intelligent systems. The program culminates with critical training in ethical and responsible AI deployment. You'll work with powerful no-code platforms including KNIME, RapidMiner, Teachable Machine, ChatGPT, Gemini, NotebookLM, and Dall E. These tools enable rapid prototyping, testing, and operationalization of machine learning models without traditional programming knowledge. Hands-On Learning Theory meets practice through 3 comprehensive projects and over 20 real-world case studies spanning hospitality, marketing and advertising, EdTech, healthcare, food and nutrition tech, and e-commerce. You'll transform raw data into actionable business insights, build classification systems, deploy neural network solutions, and create recommendation engines—all using no-code methodologies that reflect current industry practices. World-Class MIT Faculty Learn directly from MIT's leading researchers and educators, including Stefanie Jegelka, Caroline Uhler, John N. Tsitsiklis, Munther Dahleh, and Devavrat Shah. Their expertise ensures you're learning cutting-edge techniques aligned with academic research and industry application. Flexible Online Format This fully online program requires 6-12 hours weekly commitment over 12 weeks (approximately 80 total study hours). The asynchronous format allows you to balance learning with professional and personal commitments while progressing through structured modules. Upon successful completion, you'll receive a Certificat

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⌖ Barcelona

Hosted by Semrush and Euromonitor International

This in-person event will explore how AI and predictive analytics are reshaping the future of e-commerce. Experts from Semrush and Euromonitor International will discuss findings from their global study, 'The State of FMCG Ecommerce 2025', focusing on AI and data collaboration in the next era of ecommerce. The agenda includes talks by Fernando Angulo and Rabia Yasmeen, followed by networking opportunities.

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⌖ Toronto · Hyatt Regency Toronto

Hosted by TESTINGMIND

AI Engineering Summit Toronto 2026 brings 150+ practitioners together for a full day on building, deploying and scaling production AI systems. Taking place on Thursday 29 October 2026, from 9am to 5pm, this in-person summit at the Hyatt Regency Toronto is designed for people turning AI concepts into dependable software. Expect real implementation stories, practical engineering patterns and candid discussion of what it takes to move from code to production, without vendor pitches. What the summit covers The programme is single-track and practitioner-led, with sessions spanning six core themes: - Agentic development: multi-agent systems, tool calling and long-horizon autonomous workflows - AI to production: LLMOps, evaluations, cost and latency management, deployment, monitoring and operating at scale - Responsible AI: red teaming, evaluation frameworks, safety, compliance and governance - AI architecture: RAG patterns, LLM gateways, inference and AI-native system design - AI-first leadership: integrating AI into the software development lifecycle, designing teams and hiring around AI - AI data infrastructure: vector databases, embeddings and the pipelines behind intelligent systems The summit also looks ahead to emerging production standards, including agentic systems and MCP. Rather than focusing only on models or demos, it addresses the architecture, operational discipline and organisational decisions needed to make AI useful, scalable and trustworthy. Who should attend? This is a production-focused event for developers shipping AI-powered products, engineers building intelligent systems, architects responsible for scale and reliability, and technical leaders shaping organisational AI adoption. It is also relevant to compliance and governance professionals working to ensure AI systems are safe and accountable. The content is particularly suited to attendees already involved in building, operating or overseeing AI initiatives. Participants should leave with tools, patterns and informed questions they can bring back to their teams. A conference built for useful conversations… Register for this event

⌖ Toronto · Toronto, ON

Hosted by Data Engineer Things Toronto Meetup

Explore AI, scale and hard-won data engineering lessons at Shopify’s Toronto office on 29 October 2026. Running 5–8pm EDT, this in-person Data Engineer Things meetup combines technical talks with professional networking. Speakers will examine the decisions, trade-offs, mistakes and challenges involved in building modern data and AI systems, particularly where data engineering, software engineering and machine learning intersect. Talks and speakers - Derek Pyne, Staff Data Engineer at Shopify, using River to build data loops that improve models - Jill Cates, Staff Data Engineer at Shopify, whether an AI agent can identify data warehouse technical debt and verify fixes using health metrics - Mitchell Posluns and Pranavan Pirahalathan of Wealthsimple, how AI turned engineering discipline into critical infrastructure - Adeniyi Bello, Data Architect at Assent, building a zero-ETL, Go-engineered warehouse The event is designed for data, software, ML/AI, analytics and platform engineers, as well as architects and engineering leaders. Shopify is the lead sponsor, with Astronomer supporting. Registration requires host approval and closes at 11:30pm EDT on 23 October. The exact Shopify Toronto office address is shared with registered attendees. Request approval to attend

Sponsors: Shopify · Astronomer

⌖ Toronto · Amazon Toronto Office (YYZ18)

Hosted by Toronto AI Meetup

See a self-hosted AI agent query a Databricks warehouse live at TorontoAI and AWS User Group Demo Day in Toronto on 4 November 2026. This in-person demo will introduce db-agent, an open-source text-to-SQL agent that turns natural-language questions into queries. The presenter will run it against a Databricks SQL warehouse on AWS using a local LLM through Ollama, without a model API, per-question token costs or data leaving the organisation’s network. The session will cover: - What a locally hosted model handles well, and where it fails - Querying a Databricks warehouse with text-to-SQL - Privacy and cost considerations compared with metered model APIs - A read-only guardrail designed to stop destructive queries - The open-source db-agent codebase This practical session is particularly relevant to AI, data and cloud practitioners evaluating private, self-hosted approaches to enterprise data access. No broader agenda or additional speakers have been published. The event runs 6:00–8:00 PM EST on Wednesday, 4 November 2026 at Amazon Toronto Office (YYZ18), 18 York Street, Toronto. It is hosted by Chandan K. and Toronto AI Meetup, in collaboration with the AWS User Group. Registration is requested through the AWS User Group event listing. View the event and attendance details on Meetup.

⌖ Toronto · EY Tower

Hosted by The Pathfinders Network

Toronto Tech Summit 2026 brings enterprise leaders to EY Tower in Toronto on 11 November 2026 to tackle security, privacy and AI governance at scale. Engineering trust in production AI Organised by The Pathfinders Network, this one-day forum focuses on the challenge facing organisations as AI moves beyond successful pilots: how to deploy it securely, responsibly and accountably across real enterprise environments. Sessions will connect engineering decisions with cybersecurity, privacy, risk, governance and leadership priorities, grounded in Canada’s regulatory landscape and market realities. The programme combines keynotes, panel discussions and a fireside conversation covering: - Engineering trust at scale - The shadow AI crisis and governing tools organisations cannot see - AI augmentation versus workforce displacement - Cyber resilience amid AI-powered attacks - Prompt injection, poisoned pipelines and AI workflow integrity - Accountability when agentic AI takes action - Turning AI risk into business advantage The day begins with registration at 08:30, with summit sessions running from 09:00. Closing remarks are followed by a networking reception from 17:00 to 19:00. Attendees can earn up to eight hours of Continuing Professional Education credits. Speakers and the Advisory Council are still to be announced. Who should attend? Toronto Tech Summit is designed for the people responsible for building, securing and governing enterprise AI: engineers, security and privacy leaders, risk professionals and executives. It will be particularly relevant to teams moving AI systems into production, setting operational controls or balancing innovation with governance and accountability. TTS Open: prototypes, not pitch decks A distinctive part of the summit is TTS Open, a pre-event, 72-hour build competition. Multidisciplinary teams of two to four people create working MVPs with no-code, low-code or generative AI, supported by dedicated mentors. Entrants choose between two enterprise challenges: 1. Agentic AI containment, defining, enforcing and monitoring an agent’s operational boundaries, including human sign-off and automatic halt conditions. 2. The shadow AI governance gap, creating an enterprise-ready framework for visibility, enforcement and model governance without adding counterproductive friction. Attendance details The organiser’s current date is Wednesday 11 November 2026, with registration from 08:30 local time at 100 Adelaide Street West, Toronto. Check the official programme for the finishing time. View the event and registration details

Sponsors: ISC2 Toronto