Nearly every senior learner hits a session where the room seems to follow and they do not. It is usually week two or three, and it is normal.
First, separate two different problems
Wrong course. If most sessions assume coding, statistics or data engineering you do not have, you are on a practitioner track. Move to a leadership one - see AI courses for leaders vs developers.
Right course, hard week. One or two dense sessions in an otherwise suitable course. This is expected, and the fix is different.
What you must actually understand
For leadership decisions, this is the whole list:
- What the system does with data, and where that data goes.
- Why the output can be wrong, and in what way.
- Roughly what it costs to run at your volume.
- What has to be true for it to work on your data.
What you can safely skim
Model architectures. The mathematics of training. Anything about how parameters are tuned. You will never make a decision that depends on these, and no reputable programme will assess you on them.
Four things that get you unstuck
- Ask in the session. Three other people are lost and relieved you asked.
- Re-anchor to your own use case. Abstract concepts become clear the moment you apply them to a process you know.
- Ask for the business consequence. "What decision would I make differently if I understood this properly?" If the honest answer is none, move on.
- Use the recordings. In a blended format like Leading AI Innovation & Organisational Transformation, a second pass at your own pace usually settles it.
If it persists
Step back to foundations rather than pushing through. Understanding AI: What Leaders Need to Know builds the vocabulary that makes advanced material readable, and the readiness check is in am I ready for an advanced AI course.
The bottom line
Confusion in a technical session is normal and mostly harmless. Understand data, failure, cost and fit - skim the rest, and ask the question in the room. Related: what maths do I need for AI.