// APPLIED LLM ENGINEERING // FIRST EDITION // SEPTEMBER
Bridging the
AI Skills Gap.
Bridging applied research, operational AI and real industry opportunities.
14 weeks of hands-on development, enterprise AI systems and continuous project work guided by researchers and engineers.
DOWNLOAD PROGRAM ↓
Sponsored access opportunities available for selected participants.
14
WEEKS
180
TOTAL HOURS
90
HOURS IN PERSON
5
MODULES
1
CAPSTONE PROJECT
Build real AI systems hands-on
instead of Research driven...
AI Academy Direct by Fusion AI Labs is a graduate programme for applied AI designed to address one of Europe’s fastest-growing challenges: the gap between AI experimentation and operational adoption.
Built on Fusion AI Labs’ applied research methodology, the programme prepares AI professionals through applied research, real-world projects, and offers immediate employment opportunities with partner companies.
// SKILLS & OUTCOMES
Build real operational AI skills
01
Prompt Engineering
Design and evaluate prompt-based systems with verifiable quality criteria.
02
RAG Production Pipelines
Build complete pipelines from ingestion to retrieval, reordering and scalable production synthesis.
03
Multi-Tool Agents
Architect and deploy tool-calling agents and multi-agent systems using the OpenAI Agents SDK.
04
LLM Operations
Operate distributed LLM systems with structured logging, monitoring, caching and incident management.
05
When to Fine-Tune
Informed decisions on build vs. train and evaluation of fine-tuning proposals versus rapid alternatives.
06
AI Security & Governance
Prompt injection defense, release policies and production of compliant audit artifacts.
Five modules. One coherent path.
M.1
Foundation & Engineering Discipline
WEEKS 1–2
M.2
Model Behaviour & Prompting
WEEKS 3–4
M.3
Retrieval Systems & RAG
WEEKS 5–7
M.4
Tools, Agents & Orchestration
WEEKS 8–10
M.5
Production, Evaluation & Security
WEEKS 11–14
AI-assisted learning designed around real progress.
ALWAYS UP TO DATE
Materials reflect the latest field developments – validated by applied research, not static curricula.
Fusion AI Labs
via Corsica 2/18
16128 Genova
Kirill Veselkov is an Associate Professor whose research spans artificial intelligence, biomedical data science, precision medicine and precision nutrition. His work focuses on the development of clinically relevant AI and data-driven methods for decision support, patient stratification, and the integration of multi-modal health data, including clinical, lifestyle, molecular and multi-omics data. He has led and contributed to interdisciplinary research and innovation projects that translate advanced analytics into actionable insights for healthcare, prevention and personalised intervention. His work in the AIDA project advances AI for personalised medicine, while through HyperFoods he leads research into how food, metabolism, and biomarkers can be integrated to support more precise and individualised nutrition strategies. Through his research, Dr Veselkov aims to advance more predictive, preventive, and personalised approaches to health and disease.
Ricard Martínez Martínez is an Associate Professor in the Department of Constitutional Law, Political Science and Public Administration at the University of Valencia and Director of the Chair of Privacy and Digital Transformation. His work lies at the intersection between law and clinical practice, advising and training healthcare professionals and institutions on privacy, data governance and regulatory compliance in the health sector.