Generative AI
First 2027 scholarship call
Generative AI
Treat language, image, video and audio generation as a production capability, not a novelty: models chosen on criteria, reproducible parameters, review before release and provenance on every file.
Developed under the new AI Act model · Continuous updates
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)
What you'll learn
- Tell apart the families of generative models (language, diffusion, multimodal) and what each can and cannot do.
- Select models by task, cost, latency and quality, not by hype, with your own decision matrix.
- Direct text, image, video and audio generation with references and reproducible parameters.
- Build brand-consistent generation systems with reference libraries and versioning.
- Review and filter generated output before it reaches an audience, with rubrics and measurable controls.
- Manage provenance, rights, licences and transparency of synthetic content under 2026 frameworks.
- 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 — Model families
- What AI is and how it reached content generation
- Language models: how they generate text and where they fail
- Diffusion: image and video models
- Multimodal inputs: text, image, audio and video
- Choosing a model by task, cost, latency and quality
02 — Direction and control
- From creative brief to generation order
- Reference-guided generation
- Parameter control
- Reproducibility: the recipe of every asset
03 — Production systems
- Asset pipelines: from brief to delivery
- Brand consistency libraries
- Versioning prompts, models and assets
- Cost, latency and scale
04 — Quality and review
- Review controls: what the machine checks and what the person checks
- Typical failures by modality
- Evaluating with rubrics, test sets and automated judges
- Safety filters: faces, marks and sensitive content
05 — Provenance, rights and transparency
- Provenance: C2PA and Content Credentials
- Watermarks and detection
- Rights and licences: training, output, likeness and voice
- Transparency of synthetic content worldwide
06 — Capstone: multimodal pipeline with quality controls
- Designing the project pipeline
- Producing and logging
- Reviewing, signing provenance and labelling
- Delivering, operating and withdrawing
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
- · Capstone: a multimodal generation pipeline with quality, provenance and labelling controls, applied to a real brief and documented so another person can reproduce it.
Practical project: Capstone: a multimodal generation pipeline with quality, provenance and labelling controls, applied to a real brief and documented so another person can reproduce it.
Who is this for?
- · Creative and content professionals
- · Marketing and communications teams
- · Product and design roles
- · Brand owners who must approve generated content
Requirements
- · No coding required
- · A real creative brief to work on
- · Access to a spreadsheet
Meet your instructor
AI for Marketing
Chair, AI for Marketing
Generative research and content systems, multimodal generation and creative measurement.
Teaches: AI for Marketing · Generative AI
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
Verifiable certificate
200 hours · 8 academic credits
Unique verifiable code at intellcore.ai/verify
Student reviews
Reviews are published from verified students only, after the first cohort completes the program. We do not publish testimonials we cannot attribute.
