The word Gen AI is causing the heart rate of developers to go up. The immediate reactions are.
Stage 1
My job is at stake.
Stage 2
I can use this make myself better.
Stage 3
I can make this product better.
Getting to stages 2 and 3 is like seeing the light at the end of the tunnel.
But how do you to get to Stage 2 and 3?
Like it happens in every technology shift, the theory is the one that is available first. There is so much theory about Gen AI now – videos, online courses, podcasts, you name it, and it’s available.
But, to caution you, theory alone will not take a developer from Stage 1 to Stage 2 and 3.
This is where we (Nuvepro) come in. We have partnered with AWS to augment the Gen AI theory with Gen AI hands on.
These are few solutions on offer:
- Sandboxes: Did you watch a video about how Amazon Q (Code whisperer) can be used to generate a new function? Why watch when you can follow along and use our sandbox? It’s preconfigured with budget and service limits so that you can take a wrong step.
- Guided projects: Once you know the basis of Gen AI and tools, you are ready to move to Stage 2. Some projects that you can work on are:
a. Using Amazon Q to write a chat application from scratch
b. How do make an existing LLM better? By writing better prompts, fine tuning an LLM, using RAG?
c. Writing an LLM from scratch. Take your first steps in developing your own GPT or Llama LLM.
Nuvepro’s hands on learning solutions leverage AWS Bedrock and Amazon Q.
We just completed our first hands-on session where close to 80+ participants used Amazon Q to build an app to analyze Weather data.
The session went for close to 3 hours, and it was fascinating to see the participants follow along the instructions and end up creating the app. I too participated in the session. I have been a developer before, but most of what was covered in the session was new for me, especially cleansing the data, using python libraries to render the data graphically and then providing the user controls to change the visualization. And all this was done by only prompting Q to generate code. Doing all this surely led to a fanboy moment for Q. And the feeling was much better than reading about Q can help us code quicker, that’s the magic of Hands on.
Interested in jumping on to this bandwagon??
The next one is coming up this Friday, and it’s going to be even more interesting. The goal is to develop a Multimodal chat application leveraging Amazon’s bedrock models. Here’s the link to register…
Looking forward to seeing many of you there.