Advanced Hyperparameter Tuning and Model Selection Course

Advance your expertise in Bayesian HPO, multi-fidelity search, nested evaluation, multi-objective tuning and rigorous model selection.

Artificial Intelligence and Machine Learning Courses Confirmed

Advanced Hyperparameter Tuning and Model Selection Course

Training Outlines

Introduction

Advanced model tuning is an experimental-design problem, not a search for the largest validation score. Repeated comparison can overfit the validation process, waste computation and produce models that are unstable outside the development sample. Expert practice requires carefully structured search spaces, resource-aware optimisation and independent evidence for final selection.

This five-day advanced course is designed for experienced machine-learning practitioners. Participants will apply Bayesian optimisation, multi-fidelity search, population-based methods, nested validation and multi-objective selection. Technical laboratories emphasise reproducibility, uncertainty, statistical comparison and trade-offs among predictive performance, latency, robustness, fairness and cost.

Objectives

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

Design conditional and scale-appropriate search spaces.
Apply Bayesian and multi-fidelity optimisation.
Allocate computational budgets efficiently.
Conduct nested and leakage-resistant evaluation.
Optimise multiple technical and business objectives.
Compare models with uncertainty-aware evidence.
Control tuning overfit and experiment bias.
Design an advanced selection pipeline.

Course Content

Day 1: Advanced Experimental Design

Parameters, hyperparameters and search structure
Conditional and logarithmic search spaces
Validation design and nested evaluation
Search budgets and stopping rules
Reproducibility and experiment tracking
HPO experiment-design workshop

Day 2: Sequential and Multi-Fidelity Search

Random search as a strong baseline
Bayesian optimisation and surrogate models
Acquisition functions
Tree-structured Parzen estimators
Successive halving, Hyperband and ASHA
Advanced-search laboratory

Day 3: Distributed and Multi-Objective Optimisation

Parallel and asynchronous search
Population-based training
Warm starts and transfer of trials
Accuracy, latency and memory objectives
Pareto fronts and constrained tuning
Multi-objective HPO laboratory

Day 4: Model Selection and Statistical Evidence

Out-of-fold and nested estimates
Confidence intervals and paired comparison
Calibration and threshold selection
Ensembles and model diversity
Robustness and distribution-shift tests
Independent model-selection review

Day 5: Production Selection and Governance

Tuning overfit and winner’s curse
Pipeline leakage and hidden adaptivity
Model registries and evidence records
Compute cost and efficiency
Reproducible promotion and change control
Capstone advanced-selection pipeline

Training Locations

This Advanced Hyperparameter Tuning and Model Selection 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 Advanced Hyperparameter Tuning and Model Selection 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.