Artificial Intelligence AI, Uyo City meetup Saturday 4th August, 2018.
AI Saturdays Cycle 2 started on 1 August 2018. participants applications are still open. Apply here. To apply as an ambassador click here.
About
About
Known as AI6, it is a structured study group organised in 50+ cities across the globe, including Bangalore, Lagos, Toronto, Singapore and Sunnyvale. It is community-driven and free-to-attend*.
AI Saturdays (AI6) is catalysed by Nurture.AI. The first cycle of AI6 began in January 2018 and ended in May 2018. Over 5,000 participants from 50 cities worldwide were part of the AI6 movement. Motivated by the overwhelming demand and positive feedback from the AI6 community, we decided to organise a second cycle for AI6 so we can continue delivering value to those who want to learn AI.
We will be kickstarting the second cycle of AI6 in August 2018 and are currently accepting ambassador applications.
This is a story from Rowen Lee AI6 Global Coordinator
“To be honest, I didn’t expect AI6 to explode to such a scale. What impressed me even more is the amazing AI6 ambassadors who volunteered time and brainpower to nurture an AI community in their city. Not to forget the cheery participants who were passionate about learning AI despite it being a difficult subject.
Approaching the end of cycle 1, I hunted down some AI6 ambassadors and participants for a chat. I talked to an asian ambassador who has a love of teaching; a determined student from a Nigerian city that lacks AI infrastructure; an enthusiastic American researcher who, despite working full time, commits to AI6 each week. Here are some of my takeaways:
- High attrition rates were the main problem — participant count in most chapters gradually dwindled to a handful. Solutions to this varies across chapters : Bangalore aims to have 70% coding and 30% theory; Barcelona introduced quizzes using kahoot.it and hands-on coding sessions; Jabalpur requires its participants to pre-read materials before each lesson to keep everyone on the same pace; Lagos inserts interactive discussion sessions in between lectures videos.
- There is an appreciation for AI6 as a global community. Posts in the AI6 Medium publication and AI6 Slack Channel has facilitated the exchange of AI knowledge, learning materials and even tips to organise study groups. The core team hopes to continue this in the next cycle.
- Catering to a diverse audience can be challenging as AI6 participants come from diverse backgrounds; they range from yoga teachers, medical practitioners, PhD students, programmers to engineering students. There will be two different tracks in the next cycle to address this problem.
AI6 2.0!
Taking into account feedback received from the pilot cycle, the core team will roll out the following to improve the learning experience in AI Saturdays. And yes, cycle 2 is still free and open for anyone to attend!
Everyone from AI Saturdays has a story to tell — how would you tell yours?
We hope to create a community of intermediate learners on the AI6 forum, where everyone could participate in discussions to facilitate learning.
Participants and ambassadors of this track should have completed Deep learning Specialization or Fast.ai(or anything equivalent). Those who would wish to join the intermediate track but do not meet the prerequisites can catch up during the precycle (July 2018). We recommend that you use this month to complete BOTH Andrew Ng’s Machine Learning and Deep learning Specialization on coursera.
Exciting times ahead
The “perfect” time to start (or continue) your AI journey is NOW.
Think of AI as the top of a pyramid of needs. Yes, self-actualization (AI) is great, but you first need food, water and shelter (data literacy, collection and infrastructure).
Asking the right questions and building the right products
This is only about how you could, not whether you should (for pragmatic or ethical reasons).
The promise of machine learning tools
‘Wait, what about that Amazon API or TensorFlow or that other open source library? What about companies that are selling ML tools, or that automatically extract insights and features?’
All of that is awesome and very useful. (Some companies do end up painstakingly custom-building your entire pyramid so they can showcase their work. They are heroes.) However, under the strong influence of the current AI hype, people try to plug in data that’s dirty & full of gaps, that spans years while changing in format and meaning, that’s not understood yet, that’s structured in ways that don’t make sense, and expect those tools to magically handle it. And maybe some day soon that will be the case; I see & applaud efforts in that direction. Until then, it’s worth building a solid foundation for your AI pyramid of needs.
