Let me get this out of the way before we start. I love Machine Learning. I know, that's a cliché thing to say these days, with it being one of the most lucrative skills of the decade, but my passion for this field was born quite some time before the glamour of it.
It is all understandable though. 'AI is the new Electricity', afterall. I cannot gaze upon a domain and not think about how Machine Learning could optimize it, change it for the better, make it more efficient.
Fast forward a several months, me and a few of my fellow enthusiasts, were conducting workshops in our college, writing blog articles, and whatnot, just to spread knowledge about this new technology.
The Beginning
In the summer of 2019, something amazing happened. Google launched the ExploreML Facilitator program in India. I stumbled upon its announcement while browsing Linkedin(yeah, that's a thing some of us do :p). When I received the application form, I was sold. One of the requirements was that you have to take any concept, and explain it in one minute in the simplest way possible. It was at that moment, I knew that the program was aimed at people like me. Those, who have a fascination for ML, and want to teach.
My one minute explanation on Neural Networks was thankfully received well, and I was in!
Fast forward again, and I am in Bangalore for the initiation, with peers sharing my zeal for this field, and attending by top class instructors. I met brilliant people, everyone having their own stories, and some of whom went on to play a recurring part in my life.
But this post is not about the academy(You can read that in detail here). This one's about my experience teaching, and learning as a facilitator.
The First Session
As I have mentioned beforehand, I had conducted sessions on Machine Learning previously. But when you have the good name of Google attached to your workshops, the level of anticipation of the attendees, and your own expectations makes your shoulders sag with responsibility. I took time preparing for my first session, revisiting concepts that I'd been through countless times, finding something new each iteration (maybe my own brain's neural network was training on the data. Hope it didn't overfit :p). Alas, we were ready.
After coming to know that there were 400+ registrations, I found support in my friend Kiran Muthigi, who helped facilitate this session. Now, it was the D-Day, and it was the two of us and the 200+ attendees, the highest I had received ever.
It was so much fun! We went through topics from scratch, added our own content on top of ExploreML resources where we felt more explanation was needed, and went about clearing doubts. We covered basics of ML, ANNs, CNNs and much more. Having the workshop hands on did good, as people understood better, being able to see what they learnt in action.
Arguably the highlight was the last session, where I asked the attendees to pitch their own ideas, of what they would want to create with ML, and we would try to help them figure out how they would do it. There was a spark in this room, bustling with ideas, and I loved every bit of it. So did the newspaper:
Beyond ExploreML
The best thing that came out of this workshop, was a community of enthusiasts, who wanted to dive deeper, learn more. We dubbed this 'Beyond ExploreML', and over the weeks, we had multiple sessions on topics, such as Linear and Logistic Regression, Decision Trees, SVM, and many more. Every session, any member would be chosen to prepare a topic and teach it to everyone, down to the maths of it. And the roles were hence reversed, and I ended up learning a lot from those I had taught.
In these sessions and the final session in January 2020, we continued learning and teaching. The last session is particularly memorable for me. As this is my final year in college, I really wished that the ML wave only grows, and not shrinks as I step out. So this final session, the Juniors took a centre stage and taught, and seeing them teach, I know that this 'wave' is in safe hands.
Reflections
ExploreML has been a heck of a journey, and I enjoyed every bit of it. I learned a ton, not only in the domain of ML, but also how to articulate my ideas better, how to learn more efficiently. All these skills are helping me perform better at my internship, and have helped me me create better projects of my own. Having reached 500+ students through this program, I cannot think of many better learning and growing experiences.
Acknowledgments
I would like to thank Nikita Gandhi again, for all the effort she has put in this program, right from the initial arrangements, to the goodies we received for participants based on our performance, those sessions she did periodically to make sure everythings going fine, to those expert sessions on Advanced topics that helped learn so much more.
Ajinkya Kolhe, in all his frank wisdom, who has always been ready to help me out, and has become a mentor to me.
Mayank Garg for the amazing session and the sound judgements he delivered at our Hackathon.
As the program ends for this year, I wish it many, many more reruns.
Signing off,
Originally published on LinkedIn on February 26, 2020