AI Driven Predictive Maintenance and Asset Management Course

Apply AI to predictive maintenance using condition data, anomaly detection, failure prediction, remaining-life models and asset decision integration.

Artificial Intelligence and Machine Learning Courses Confirmed

AI Driven Predictive Maintenance and Asset Management Course

Training Outlines

Introduction

Predictive maintenance uses condition data and machine learning to identify deterioration before functional failure. Its value depends on more than predicting breakdowns: organisations must connect sensor evidence to failure modes, maintenance actions, production risk and asset economics. Poor labels, rare failures and excessive false alarms can quickly undermine trust and operational value.

This five-day course combines asset-management judgement with applied AI. Participants will prepare condition-monitoring data, develop anomaly, failure and remaining-life models, define actionable thresholds and integrate predictions with maintenance planning. The course is designed for maintenance, reliability, asset and analytical professionals working with real industrial constraints.

Objectives

By the end of this course, participants will be able to:

Select assets and failure modes for predictive maintenance.
Prepare sensor, event and maintenance-history data.
Engineer meaningful condition and degradation features.
Apply anomaly, failure and remaining-life models.
Evaluate predictions using maintenance consequences.
Convert model outputs into maintenance actions.
Integrate AI with CMMS and asset processes.
Develop a governed predictive-maintenance roadmap.

Course Content

Day 1: Asset Strategy and Predictive Use Cases

Corrective, preventive and predictive maintenance
Asset criticality and consequence analysis
Failure modes and degradation mechanisms
Condition indicators and intervention points
Sensor, alarm and work-order data
Predictive-maintenance use-case workshop

Day 2: Condition Data and Feature Engineering

Sampling, synchronisation and operating context
Missing data and sensor-quality checks
Windowing and signal summarisation
Trend, frequency and health features
Failure labels and censored observations
Condition-data preparation laboratory

Day 3: Predictive Maintenance Models

Anomaly and novelty detection
Failure classification and risk scoring
Remaining useful life estimation
Survival and time-to-event modelling
Rare failures and imbalanced data
Asset-model development laboratory

Day 4: Maintenance Decisions and Value

Alert thresholds and lead time
Uncertainty and maintenance prioritisation
CMMS and EAM integration
Maintenance scheduling and spare planning
False alarms and human diagnosis
Reliability business-case exercise

Day 5: Deployment and Asset Governance

Edge, cloud and hybrid monitoring
Sensor and model drift
Performance and avoided-failure tracking
Retraining and alert change control
Ownership and operational escalation
Capstone predictive-maintenance solution

Training Locations

This AI Driven Predictive Maintenance and Asset Management Course is available in multiple cities. Please select your preferred location from the list below

Durrës

Albania

Tirana

Albania

Andorra la Vella

Andorra

Escaldes-Engordany

Andorra

Innsbruck

Austria

Salzburg

Austria

Vienna

Austria

Gomel

Belarus

Minsk

Belarus

Antwerp

Belgium

Brussels

Belgium

Banja Luka

Bosnia and Herzegovina

Sarajevo

Bosnia and Herzegovina

Plovdiv

Bulgaria

Sofia

Bulgaria

Dubrovnik

Croatia

Split

Croatia

Zagreb

Croatia

Limassol

Cyprus

Nicosia

Cyprus

Brno

Czech Republic

Prague

Czech Republic

Aarhus

Denmark

Copenhagen

Denmark

Tallinn

Estonia

Tartu

Estonia

Helsinki

Finland

Tampere

Finland

Lyon

France

Marseille

France

Nice

France

Paris

France

Berlin

Germany

Frankfurt

Germany

Hamburg

Germany

Munich

Germany

Athens

Greece

Thessaloniki

Greece

Budapest

Hungary

Debrecen

Hungary

Akureyri

Iceland

Reykjavík

Iceland

Jakarta

Indonesia

Cork

Ireland

Dublin

Ireland

Florence

Italy

Milan

Italy

Naples

Italy

Rome

Italy

Osaka

Japan

Tokyo

Japan

Pristina

Kosovo

Prizren

Kosovo

Liepāja

Latvia

Riga

Latvia

Schaan

Liechtenstein

Vaduz

Liechtenstein

Kaunas

Lithuania

Vilnius

Lithuania

Esch-sur-Alzette

Luxembourg

Luxembourg City

Luxembourg

Kuala Lumpur

Malaysia

Malé

Maldives

St. Julian's

Malta

Valletta

Malta

Bălți

Moldova

Chișinău

Moldova

La Condamine

Monaco

Monte Carlo

Monaco

Budva

Montenegro

Podgorica

Montenegro

Amsterdam

Netherlands

Rotterdam

Netherlands

The Hague

Netherlands

Abuja

Nigeria

Lagos

Nigeria

Port Harcourt

Nigeria

Ohrid

North Macedonia

Skopje

North Macedonia

Bergen

Norway

Oslo

Norway

Gdańsk

Poland

Kraków

Poland

Warsaw

Poland

Faro

Portugal

Lisbon

Portugal

Porto

Portugal

Bucharest

Romania

Cluj-Napoca

Romania

City of San Marino

San Marino

Serravalle

San Marino

Belgrade

Serbia

Novi Sad

Serbia

Singapore

Bratislava

Slovakia

Košice

Slovakia

Bled

Slovenia

Ljubljana

Slovenia

Incheon

South Korea

Seoul

South Korea

Barcelona

Spain

Madrid

Spain

Valencia

Spain

Sri Jayawardenepura Kotte

Sri Lanka

Gothenburg

Sweden

Stockholm

Sweden

Bern

Switzerland

Geneva

Switzerland

Zurich

Switzerland

Kaohsiung

Taiwan

Taipei

Taiwan

Ankara

Turkey

Istanbul

Turkey

Kyiv

Ukraine

Lviv

Ukraine

Odesa

Ukraine

Dubai

United Arab Emirates

Birmingham

United Kingdom

Edinburgh

United Kingdom

London

United Kingdom

Manchester

United Kingdom

Rome (Vatican-adjacent)

Vatican City

Training Schedule

Below is the table of cities along with the respective dates for the upcoming training sessions of AI Driven Predictive Maintenance and Asset Management Course. Please review the schedule to find the most convenient option for you. You can also use the below search bar to type the city name and filter the results.