Generative AI Foundations
A rigorous but accessible tour of how modern generative models work — tokenization, attention, pre-training, alignment — and the ecosystem around them: model families, hosting options, cost models and capability boundaries. Sets the conceptual base for every LLM engineering course that follows.
What this course covers.
5 modules, 33 named skill atoms. Expand any module to see them.
1From N-grams to Transformers6 skill atoms
2Inside an LLM7 skill atoms
3Training & Alignment7 skill atoms
4Model Landscape6 skill atoms
5Hands-on Playground7 skill atoms
AI-107 in the role journeys.
This course appears in 7 of our 45 role journeys. Here is what a learner takes immediately before and after it in each.
Roles this course serves
This course is authored to band B2.
Every course we run is written to one rung of the CASI ladder, so a plan can be assembled to take a team from where they are to where they need to be.
What do B1–B6 mean?The CASI Capability Ladder — click to expand
Every course targets a band on the CASI Capability Ladder — our six-band proficiency scale, anchored to open standards (O*NET, ESCO, NICE, NIST AI RMF, Bloom's). A band tells you how deep a course goes, and what evidence proves it.
A note on B6. Courses in this catalog target B1–B5. B6 is not taught — it is recognised, through a portfolio and a panel, once someone is setting direction for others. Every journey here is built to land a learner at B5.
Other AI courses at this level.
Python for AI Engineering
Mathematics & Statistics for Machine Learning
Data Wrangling & EDA with pandas
SQL & Data Foundations for AI Teams
Prompt Engineering Essentials
Visualization & Data Storytelling
Run AI-107 for your team.
This course runs at several lengths depending on how deep you need to go and how much of it your people already have. Tell us who is being trained and we will scope it.