Professional Certificate in Applied Prompt Engineering & AI Workflow Automation
This page is the single official record of this programme. Transcripts, syllabus PDFs, the learner workspace and the public verification page are all generated from it, and each printed syllabus carries the version and fingerprint shown below so evaluators can compare them line by line.
Each module is 60 hours: 20 h guided instruction, 20 h supervised lab, 12 h project studio, 8 h assessment. Programme version 2026.10 · fingerprint 2BACA5963014BC67
| Code | Course | Hours | ECTS |
|---|---|---|---|
| SWY-14-M01 | Foundations of Large Language Models | 60 | 3 |
| SWY-14-M02 | Core Prompt Engineering Patterns | 60 | 3 |
| SWY-14-M03 | System Prompts & Context Management | 60 | 3 |
| SWY-14-M04 | Structured Outputs & Tool Calling | 60 | 3 |
| SWY-14-M05 | Retrieval-Augmented Generation | 60 | 3 |
| SWY-14-M06 | AI Agents & Orchestration | 60 | 3 |
| SWY-14-M07 | Multimodal AI | 60 | 3 |
| SWY-14-M08 | Building AI Apps with Lovable | 60 | 3 |
| SWY-14-M09 | AI Safety, Ethics & Governance | 60 | 3 |
| SWY-14-M10 | Capstone — Deployed AI Workflow Product | 60 | 3 |
M01 Foundations of Large Language Models · Module 1 · 60 h
Tokens, transformers, model families, capabilities and limits, hallucination.
- • Tokens
- • transformers
- • model families
- • capabilities and limits
- • hallucination
M02 Core Prompt Engineering Patterns · Module 2 · 60 h
Role, context, task, format; few-shot, chain-of-thought, self-critique.
- • Role
- • context
- • task
- • format
- • few-shot
- • chain-of-thought
- • self-critique
M03 System Prompts & Context Management · Module 3 · 60 h
Instruction hierarchy, context windows, memory, prompt testing and versioning.
- • Instruction hierarchy
- • context windows
- • memory
- • prompt testing and versioning
M04 Structured Outputs & Tool Calling · Module 4 · 60 h
JSON schemas, function calling, validation, error recovery.
- • JSON schemas
- • function calling
- • validation
- • error recovery
M05 Retrieval-Augmented Generation · Module 5 · 60 h
Embeddings, vector search, chunking, grounding and citation.
- • Embeddings
- • vector search
- • chunking
- • grounding and citation
M06 AI Agents & Orchestration · Module 6 · 60 h
Planning loops, multi-step agents, human-in-the-loop review.
- • Planning loops
- • multi-step agents
- • human-in-the-loop review
M07 Multimodal AI · Module 7 · 60 h
Image, speech and document understanding; image and audio generation.
- • Image
- • speech and document understanding
- • image and audio generation
M08 Building AI Apps with Lovable · Module 8 · 60 h
Prompting a full-stack app in Lovable, adding a database, sign-in and AI features, publishing.
- • Prompting a full-stack app in Lovable
- • adding a database
- • sign-in and AI features
- • publishing
M09 AI Safety, Ethics & Governance · Module 9 · 60 h
Prompt injection, data privacy, bias, ISO/IEC 42001, NIST AI RMF.
- • Prompt injection
- • data privacy
- • bias
- • ISO/IEC 42001
- • NIST AI RMF
M10 Capstone — Deployed AI Workflow Product · Module 10 · 60 h
A published, documented AI application solving a real workplace problem.
- • A published
- • documented AI application solving a real workplace problem
- • Written examination — 30% of the course mark
- • Laboratory / practical portfolio — 40% of the course mark
- • Project defence — 20% of the course mark
- • Professional conduct & participation — 10% of the course mark