AI Automation

Design intelligent workflows and agentic systems that run reliably inside real operations.

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

Map a process and identify what should and should not be automated.
Design the end-to-end architecture: triggers, system of record, integrations, orchestration and state.
Design tool schemas, planning loops and state management for multi-step tasks.
Add guardrails, retries, fallbacks and human oversight.
Monitor reliability and cost once the flow is in production, with continuous evaluation.
Roll the flow out in phases and measure time saved against a baseline.
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 — Process mapping

What AI is and how it reached process automation
Mapping the as-is process
Decision points: rules, judgement and data
Exception paths
Limits of automation: what to automate and what not

02 — End-to-end automation architecture

Triggers, events and the system of record
Integrations: APIs, files, queues and RPA
Orchestrators and durable state
The flow without an agent first: extraction, validation and bounded models

03 — Agentic systems inside the process

Tool calling and tool schemas
Plan-and-execute loops
Memory and state in multi-step tasks
Identity, permissions and protocols: the agent inside the process

04 — Reliability engineering

Input, action and output guardrails
Retries, idempotency and fallbacks
Human checkpoints
Failure modes and escalation paths

05 — Operations: observability, cost and evaluation

Observability: traces, metrics and logs
Cost control
Continuous evaluation
Incidents, changes and continuous improvement

06 — Go-live and final project

Gradual rollout: shadow, canary and stop
Measuring value: time saved and quality
Governance and compliance of automation
Final project: the flow in production

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 with the IntellCore AI Act Method™: from system records to the review plan

Practical application

· Final project: a working automated flow with guardrails and human checkpoints, with its go-live file, time saved measured against the baseline and a live stop-switch test in the defence.

Practical project: Final project: a working automated flow with guardrails and human checkpoints, with its go-live file, time saved measured against the baseline and a live stop-switch test in the defence.

Who is this for?

· Operations and process leads
· Technical and semi-technical profiles
· Consultants and internal AI leads

Requirements

· Comfort with workflow tools
· Basic data literacy

Meet your instructor

AI Agents & Automation

Chair, AI Agents & Automation

Tool calling, planning loops, state handling, guardrails and human-in-the-loop checkpoints.

Teaches: AI Automation

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