The Spark of Micro-Teaching: Simplifying Machine Learning for All 🤖✨

 The Spark Behind the Session: A Personal Take on AI Teaching

Imagine standing at the edge of a topic as broad and complex as Machine Learning, and having just 15 minutes to bring it alive for your peers. That’s the challenge—and the charm—of microteaching. 

As part of my ED403 experience, I delivered a session titled "Introduction to Machine Learning" under the EE461 Special Topics course. My goal? Make machine learning understandable, practical, and relevant—even to those hearing about it for the first time.

Machine learning in industry - ATRIA Innovation 

The Plan: From Data to Decisions in 15 Minutes

Microteaching isn’t about covering everything—it’s about doing something meaningful with precision. I structured my session around the basics: what machine learning is, how it differs from traditional programming, and how we see it daily in spam filters, voice assistants, and fraud detection systems.

Using MATLAB’s classification workflow, I broke down the 6 essential stages: data loading, preprocessing, feature extraction, model training, validation, and prediction. Each step was supported with real-life examples and simplified visuals, making the abstract tangible. My favorite part? Demonstrating how machines learn from patterns without being explicitly programmed—pure magic!

The Joys and the Jitters: Performance Meets Passion

Delivering the content in such a short time was both thrilling and nerve-wracking. Every slide had to be purposeful. I worked on pacing, integrated interaction prompts, and used relatable analogies. The feedback I received from my peers and observer was insightful—it helped me understand the power of enthusiasm and the value of clarity when introducing technical subjects.

Lessons Learned: Microteaching as a Teaching Superpower

This experience was more than a presentation—it was a reminder that even the most complex subjects can be made approachable with the right planning. I walked away not just more confident about the topic but also more mindful of learner needs, engagement strategies, and how to align delivery with learning outcomes.

Gratitude Note

A big vinaka vakalevu to my team and CC: Dr. Shikha for their support and feedback. Your observations helped me refine my content and grow as a teacher. Also, a shoutout to all my peers—your sessions inspired me and made this journey collaborative and exciting.

PS: I might reach out to you guys for expert advice if I plan to make some investments in near future 😆

Until next time, may your algorithms converge and your learning never stop. 🚀


Cheers,
Krish.

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