CLP 180.000
Generative AI Foundations: A Hands-On Workshop
A one-day workshop covering how large language models work, where they fail, and how to use them responsibly in professional settings.
View detailsDeep Learning — Live Events
Where theory
Where theory
meets practice
in the room
Workshops, seminars, and intensive sessions on deep learning techniques — structured for practitioners who want to work through real architectures, not just hear about them.
5+ Upcoming events
8h Avg. session depth
3k Attendees to date
Scheduled events
All sessions include hands-on work with real model architectures and datasets.
CLP 240.000
AI Image Generation for Visual Professionals
A three-session course for graphic designers, art directors, and illustrators working with Midjourney, Stable Diffusion, and DALL-E in client projects.
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CLP 320.000
Building AI Writing Workflows for Content Teams
A practical two-day course for content managers, editors, and writers on integrating generative AI into editorial processes without losing quality control.
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CLP 95.000
Generative AI in Data Analysis: A Half-Day Seminar
A focused seminar for analysts and researchers on using AI-assisted tools for data interpretation, report generation, and exploratory analysis.
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CLP 210.000
Generative AI Ethics and Organizational Governance
A one-day event for managers, policy leads, and HR professionals on building internal frameworks for responsible AI use in organizations.
View detailsAttendance trends
Participation has been growing steadily since 2024
Each session draws a more technically prepared audience. Attendees arrive having already worked through foundational material — which shifts the conversation toward architecture decisions, training dynamics, and debugging strategies rather than definitions.
The chart reflects cumulative registrations across all event formats — workshops, intensive labs, and panel sessions — tracked monthly.
- Workshops fill within 6–9 days of announcement on average
- Repeat attendance across multiple events sits at roughly 38%
- Most registrations come from practitioners already in industry roles
Registrations — monthly cumulative
Registrations 2024
Latest data point
What shapes each session
Defined scope
Each session targets one specific technique — transformer fine-tuning, diffusion model inference, or gradient flow debugging — rather than surveying an entire field.
Prerequisite clarity
Prerequisites are listed explicitly. If an event requires familiarity with backpropagation and PyTorch basics, that is stated — not implied.
Working code included
Participants leave with notebooks they actually ran — not slides. The code is commented for post-session reference, not for presentation aesthetics.
Small group format
Sessions cap at 24 participants. That limit exists so questions get answered and instructors can observe how people work through problems in real time.
Stay ahead of
the next session
Events are announced 3–4 weeks in advance and fill quickly. Leaving your contact means you hear about new sessions before they go public.
No newsletters, no promotional emails. Announcements only — one message per event.