I’ve been sharing quite a bit about generative AI over the last few emails… And rightly so, the data industry is in the process of being buried overnight by the number of needs and opportunities around generative AI use cases.
On top of this staggering demand, the supply of talent isn’t even enough to make a dent… and a lot of us data professionals are already at capacity with the more traditional data work that we’ve been occupied with over the last few years.
For busy data and tech professionals, it’s a daunting task to learn a whole new application area while also working to maintain our current requirements. I get it.
But, it can be done. And it should be done.
So, in today’s email I want to share some learning resources that I’m using to get up-to-speed in Gen AI with minimum downtime.
Free Generative AI Courses
[LONG FORM] Fundamentals of Generative AI for Real-World Applications: I had the incredible good fortune to spend some time speaking to Chris Fregly yesterday (he’s a very capable Generative AI Solution Architect at AWS - and a stellar person, to boot!). I believe he’s a contributor to this course, but in any case, he suggested that as a must-have long-form course to get up-to-speed on Generative AI. I believe it’s about 5 hours long, and FREE - something we can watch passively and learn from without going down the rabbit hole too deep.
[SHORT-FORM] Courses on DeepLearning.ai - There are 9 free short-form courses on AI engineering and the build of generative AI products over on DeepLearning.AI. All of them only require basic Python and shouldn’t take more than a few hours to work through.
[MIXED LENGTH] Cohere’s LLM University - Cohere offers a comprehensive NLP curriculum at LLM University. From the fundamentals of LLMs all the way to the most advanced topics, including generative AI. It’s definitely worth a gander.
To be honest, I’m learning about training resources faster than I can actually use them. Who would like to join me for a 100 days of generative AI challenge - so we can support one another and hold each other accountable?
Gen AI Live Training
Early this week, I shared a free live workshop that was hosted by SingleStore, wherein they were teaching how to build a no-code gen AI product in flowise.ai. It looks like they had about 2.4k sign-ups, where 600 learners showed up live!
Tomorrow they’re hosting another live training on Fast AI on JSON: Using OpenAI to Build a Real-Time Recommendation Engine
Join this training for a live hands-on session on how to build a real-time conversational AI recommendation engine using OpenAI and ChatGPT.
For this session, they’ll be utilizing JSON data within MongoDB® and will use SingleStore Kai™ to do semantic search and fast analytics to power a real-time recommendation engine.
What you’ll learn:
How to use OpenAI vector embeddings to do semantic search on JSON data in order to build a real-time conversational AI and recommendation engine
Discover SingleStoreDB’s native support for vector functions to power semantic search and Generative AI with simple SQL queries
How to analyze JSON data within MongoDB ultra-fast using SingleStore Kai™ (MongoDB® API) without any query changes
How to do complex analytics on JSON to build a “conversational AI” recommendation engine that you can speak to
TIME / DATE: Thursday, August 24th, 10:00am PDT
Replays are available if you sign up for the event now.
100 Days of Generative AI Challenge
If you’d like to discuss forming a small accountability group wherein we can support each other in getting upskilled in Gen AI, please reply back and I will get back to you privately. I already have a few friends who’ve expressed interest…
Cheers,
Lillian
(This post contains some bits of sponsored content. That said, nothing I have shared here requires to you to pay anything to learn from…)
Dear Lillian,
I would like to discuss about the formation of a small accountability group wherein we can support each other in getting upskilled in Gen AI as mentioned by you previously. Hoping to hear back from you soon with a positive response.
Cheers
Fatima