About this Event
Workshop Overview
Our April workshop takes students beyond building AI projects into the next critical stage of innovation: improving, refining, and scaling intelligent systems. This is where learners experience how real developers work, testing, debugging, and enhancing their creations to make them more accurate, creative, and reliable.
Participants revisit the AI systems they built in March and transform them into more polished, production-ready solutions. It’s an exciting shift from “it works” to “it works better, smarter, and more creatively.”
In the Beginner Track, students upgrade their AI-powered Scratch games by identifying and fixing bugs, then enhancing their projects with sounds, scoring systems, costumes, and clear win/lose conditions. They learn how small improvements can dramatically elevate a user experience.
In the Advanced Track, students take their Python chatbots to the next level by introducing multi-turn conversations, memory, and branching dialogue paths. Their chatbots evolve from simple responders into more intelligent systems capable of holding richer, more human-like interactions.
This workshop reinforces an important lesson: great technology is built through iteration, not perfection.
This workshop is FREE, and all learning materials are provided, students simply need to bring curiosity and a willingness to improve and innovate.
Beginner Track – AI Game Enhancement
This is where students transform their projects from basic prototypes into engaging, polished games. Using their AI-powered Scratch games from March, learners debug issues and introduce new features that improve both functionality and creativity.
Students will explore how real developers enhance user experience by refining performance, fixing bugs, and adding meaningful features.
Key Activities
- Understanding what bugs are and why they occur
- Learning the 5-step debugging strategy (Read, Test, Check, Ask, Google)
- Loading and reviewing March AI games
- Identifying and fixing errors
- Selecting 3–5 enhancements from an upgrade menu
- Adding sounds, costumes, scoring systems, and timers
- Creating clear win/lose conditions
- Partner testing and feedback
Learning Outcomes
Students will:
- Define debugging and identify common coding issues
- Apply structured problem-solving techniques
- Enhance games with sound, visuals, and interactivity
- Use variables to build scoring systems
- Design clear game logic (win/lose conditions)
- Test projects and provide constructive feedback
Materials Needed
Black Boys Code will provide guidance and structured support throughout the session.
- Laptop with internet access
- Scratch account
- Saved AI games from March
- Enhancement checklist
- Testing and feedback forms
Deliverables
- Enhanced AI-powered game with 3+ new features
- Bug report and fix documentation
Advanced Track - Chatbots & Conversation Design
Students evolve their chatbots from simple programs into intelligent conversational systems. Using Python, learners design chatbots that can handle multi-step conversations, remember context, and guide users through different dialogue paths.
This is where coding meets real-world AI design, as students begin to understand how assistants, customer support bots, and interactive systems are built.
Key Activities
- Understanding dialogue trees and conversation flow
- Learning how chatbots track context using variables
- Implementing nested conditionals for branching conversations
- Creating multi-turn conversations (2–3 turns minimum)
- Adding memory and follow-up question logic
- Designing flowcharts for conversation paths
- Testing all dialogue branches
- Partner testing and feedback
Learning Outcomes
Students will:
- Understand how conversational AI systems are structured
- Apply nested conditional logic effectively
- Build multi-turn, interactive conversation flows
- Track user context using variables
- Design branching dialogue experiences
- Systematically test and refine chatbot behavior
Materials Needed
Black Boys Code will provide guidance and structured support throughout the session.
- Laptop with internet access
- Replit account (free tier)
- Python chatbot from March
- Dialogue-tree planning templates
- Nested conditional examples
- Testing documentation tools
Deliverables
- Enhanced chatbot with multi-turn conversations
- Dialogue-tree flowchart
- Test-path documentation
- Bug report and fixes
If you’re unsure who your Chapter Leader is, please contact [email protected] to get connected and learn how you can support your local team.
For further questions you may have on the day of the workshop, please reach out to [email protected]
Register Now, Space Is Limited!
Event Venue & Nearby Stays
University of New Brunswick: Brydone Jack Observatory Museum, 10 Bailey Drive, Fredericton, Canada
CAD 0.00
