IBM watsonx.ai Technical Sales Workshop
This workshop covers the IBM watsonx.ai L3 badge lab, highlighting some of the core components and capabilities of IBM watsonx.ai with additional L3+ labs that can be included based on client interest.
Prerequisites and FAQs
Classroom style workshops will typically provide a shared watsonx.ai environment to be utilized for the workshop. However, freely available tech zone and IBM cloud services are available to business partners to facilitate these labs independently.
Labs
watsonx.ai Technical Sales Intermediate (L3) badge lab
- The watsonx.ai web based Prompt Lab UI, including Structured and Freeform interface, sample prompts, model information panels and model parameter panel.
- Strengths and weaknesses of different models
- An overview of the model parameters and how they influence output.
- Zero shot vs. Few shot prompting
- Using prompts to generate specific output
- Saving prompts and prompt sessions
- Restoring a prompt to an earlier state via prompt history
- Saving prompts to a Jupyter notebook and working with the Jupyter notebook
Watsonx.ai is being developed and released in an agile manner, which may result in some of the lab screenshots looking slightly different from what you see in the UI. You may notice the following differences:
- Additional foundation models in the library list
- Tweaks to the user interface (location of buttons, text/labels for various fields)
- Additional tabs/buttons (especially when the Tuning Studio is released).
None of the above changes should impact the labs in this document. However, there are a few possible changes that would compromise the integrity of the lab:
- Ongoing tuning of the foundation models may result in varied results.
- Updates to the sample prompt default text may change. The original text for all prompts has been provided in the lab document if you need to copy/paste to the prompt UI.
Labs L3
101: Navigation and zero shot prompting
Last updated 1 year ago
Explore the watsonx.ai console
102: Parameter config and output formats
Last updated 1 year ago
Understand the parameters available within the Prompt Lab
103: One-shot prompts, saving prompts
Last updated 1 year ago
See how to use one-shot prompting and saving prompts for future use
104: Using Notebooks
Last updated 1 year ago
Use Jupyter notebooks to interact with watsonx.ai programmatically
Supplemental labs (L3+)
Supplemental Labs L4
201: Introduction to Generative AI in watsonx.ai
Last updated 9 months ago
202: Large language model application building blocks
Last updated 9 months ago
203: LangChain
Last updated 9 months ago
204: Implement RAG Use Cases
Last updated 9 months ago
205: RAG on documents with LangChain and Elasticsearch
Last updated 8 months ago
206: Prompt Tuning
Last updated 7 months ago
207: Generate synthetic data
Last updated 7 months ago