Black Boys Code Ottawa - Training the Machine

Sat Feb 28 2026 at 10:00 am to 02:00 pm UTC-05:00

Louis-Pasteur Private | Ottawa

Black Boys Code
Publisher/HostBlack Boys Code
Black Boys Code Ottawa - Training the Machine
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Join us for an exciting workshop designed just for boys aged 8-12! Whether they’re brand new to coding or eager to level up their skills.
About this Event

Workshop Overview

In celebration of Black History Month, this workshop invites students to explore how diversity, culture, and representation influence the technologies shaping our world today. Students learn that Artificial Intelligence is not neutral—it reflects the data it is trained on—and that inclusive data leads to smarter, fairer, and more accurate AI systems. Through hands-on learning and real-world examples, learners discover how machines recognize faces, emotions, and language, and why it is important that all communities are represented in the digital future. In the Beginner Track, students train an emotion-recognition AI model using images and expressions, gaining firsthand experience in how data quality and diversity affect machine learning outcomes, while in the Advanced Track, students design the personality, purpose, and conversation flow of a chatbot using prompt engineering and blueprint planning, laying the foundation for building intelligent, responsible, and user-friendly AI systems in future workshops.

This workshop is FREE, and all learning materials are provided.



Beginner Track – AI & Data Training

Theme: Learning Through Data

Students dive deeper into AI training by creating a more sophisticated emotion-detection model. They learn the critical concept that AI learns from data — the more examples you give it, the smarter it becomes. Students explore what makes good data vs. bad data and understand why diversity in training examples matters. The session focuses on building a 3–4 class emotion recognition model (Happy, Sad, Surprised, and optionally Angry).


Key Activities
  • Reviewing Month 1 progress
  • Learning about data quality (lighting, angles, backgrounds)
  • Collecting 20–30 photos per emotion class
  • Training emotion detection model with proper data
  • Testing model accuracy with different expressions
  • Exporting trained models for next month


Learning Outcomes

Students will:

  • Understand how AI learns from data
  • Recognize the importance of diverse training data
  • Collect and organize quality training images
  • Train a 3–4 class emotion detection model
  • Test and evaluate model accuracy


Register Now, Space Is Limited!

For further questions you may have on the day of the workshop, please reach out to [email protected]

Or [email protected]

Register Now, Space Is Limited!


Event Photos
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Event Venue & Nearby Stays

Louis-Pasteur Private, Louis-Pasteur Private, Ottawa, Canada

Tickets

CAD 0.00

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