AI for Food Bioprocesses

A fermented batch, told to someone who has never seen a fermenter. The model proposes. The learner neither doses nor releases.

Developed under the new AI Act model · Continuous updates

IntellCore campus app, available on iOS and Android

Edition 2026

200 hours of applied learning

8 academic credits

25 lessons + 6 workshops

Digital campus

Verifiable certificate

550 USD one payment · or 2 × 275 USD (today and after 30 days)

Enroll here

What you'll learn

Describe a batch without acronyms: tank, feed, time and product.
Read temperature, acidity and feed, and know why the point is closed by the sample, not the model.
Tell CCP, process and procedure deviations apart in a food bioprocess.
Keep the model’s feed increase as a proposal, never an order, with its log entry and status.
Recognise and withdraw typical failures: chat recipes, entries without measures and disguised proposals.
Write a sheet that reads without the chat, with the dosing signature left empty.
Apply the IntellCore AI Act Method™: classify the risk of an AI use case in your field and document it under the AI Act 2026.

Program curriculum

01 — The place

What AI is and how it reached food bioprocesses
Tank, feed, time and product
Three ways to run the batch
Who loads, who watches, who releases
Your role

02 — The number that already exists

Temperature, acidity and feed
The sample that arrives late
The four-hour point
What a deviation would be

03 — Where the model may propose

What the model asks for
Why 8 % is not an order
What is missing
Log and wait

04 — The tool

The next hour
The copy of the tank
What it does not see
When the sample comes back

05 — The failure

The recipe in the chat
No time, no measure
The disguised proposal
What gets withdrawn

06 — The batch record

From the point to the batch
What could be changed
Who releases
The next-day sheet

07 — IntellCore AI Act Method™ applied to your field

The EU AI Act 2026: risk levels, prohibited practices and obligations
Transparency, human oversight and documentation in your professional field
Classifying and auditing a real AI use case step by step
Your compliance file: certified with the IntellCore AI Act Method™

Practical application

· Final project: the batch sheet for lot L-0417, with the data, the 8 % feed proposal, what was not checked and an empty dosing signature, plus the next-day sheet that reads without the chat and is defended in five minutes.

Practical project: Final project: the batch sheet for lot L-0417, with the data, the 8 % feed proposal, what was not checked and an empty dosing signature, plus the next-day sheet that reads without the chat and is defended in five minutes.

Who is this for?

· Anyone who will read a fermented batch sheet
· Food, quality and production teams without plant vocabulary
· Analysts who review model proposals

Requirements

· No prior plant experience
· No coding required
· About 6 hours per week

Meet your instructor

AI for Food Bioprocesses

Chair, AI for Food Bioprocesses

Fed-batch fermentation, probe and lab data, feed proposals and the batch record — the model proposes, the person neither doses nor releases.

Teaches: AI for Food Bioprocesses

Edition 2026

What each week includes

Every week of the program follows the same structure.

01
Explainer video per lesson
02
Guided reading (6 h)
03
IntellCore Labs · ~90 min workshop with data
04
Verified real case
05
IntellCore Podcast
06
IntellCore Radar
07
Self-assessment
08
Practice and exam (70%, 3 attempts)
09
Extended practice (5 h)
10
IntellCore AI Act Method™ module applied to your field (30 h)
11
Applied final project (30 h)
12
6 modules × 23 h + IntellCore AI Act Method™ module 30 h + final assessment 2 h + final project 30 h = 200 h
13
Downloadable PDF summary