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Automated Machine Learning (AutoML) – Level 5 Course

 

Develop a broader understanding of Automated Machine Learning with Oxford Home Study Centre. This Level 5 online programme examines AutoML across the machine-learning lifecycle, including data preparation, model building, hyperparameter optimisation, evaluation, deployment and domain-specific applications.

The programme has an estimated duration of 450 hours and is designed for flexible, self-paced study. You can browse our complete online course catalogue or compare related programmes in our artificial intelligence course collection.

AutoML platforms automate selected stages of machine-learning development. Depending on the tool, this can include data preparation, model search, training, hyperparameter tuning, evaluation and deployment support.

This programme takes a structured approach to those stages. You will begin with the role of AutoML in machine learning and the features of different platforms before moving into preprocessing, automated model building, tuning, validation and deployment.

The course also examines an important limitation of automation: an automatically generated model is not automatically a good model. Data quality, target definition, metric selection, validation, bias checks and human oversight remain essential throughout the lifecycle.

Later modules consider deployment and advanced AutoML applications across different sectors. The emphasis is on understanding how automation can support machine-learning workflows without removing the need for informed technical and organisational decisions.

 

Who Should Study This Course?

 

The programme may suit data analysts, data scientists, AI and machine-learning learners, software developers, business analysts, IT professionals, researchers and students who want a more substantial treatment of automated machine learning.

The course is educational and is not a substitute for vendor-specific platform certification or practical project experience.

 

What You Will Learn

  • Explain AutoML and its relationship to traditional machine-learning workflows.
  • Compare the purpose and capabilities of AutoML platforms.
  • Prepare data for automated model development.
  • Understand automated model building and training.
  • Explore hyperparameter optimisation and tuning.
  • Evaluate and validate AutoML-generated models.
  • Understand deployment and integration considerations.
  • Explore advanced AutoML applications across different domains.

If you want a shorter introduction first, our free Using AutoML Tools course is a Level 3, 200-hour route covering AutoML foundations, platform concepts and data preprocessing.

This Level 5 programme is the broader route, extending across eight modules into model building, hyperparameter optimisation, evaluation, validation, deployment and advanced domain applications.

 

Useful Machine-Learning Guides

 

If you want to refresh the underlying concepts before starting, our beginner's guide to machine learning explains the core ideas behind data, models and learning from examples.

For a broader view of the stages around model development and deployment, read our guide to the AI model lifecycle.

 

Frequently Asked Questions

 

What is Automated Machine Learning?

 

Automated Machine Learning uses software to automate selected tasks involved in developing machine-learning models, potentially including preprocessing, model selection, tuning, evaluation and deployment support.

 

What level is this AutoML course?

 

This is a Level 5 course with an estimated duration of 450 hours.

 

Does the course cover AutoML platforms?

 

Yes. Module 2 explores AutoML platforms, their features and their role in accelerating model-development workflows.

 

Will I learn to build and train models with AutoML?

 

Yes. Module 4 focuses on automated model building and training concepts.

 

Does the course cover hyperparameter optimisation?

 

Yes. Module 5 examines automated hyperparameter optimisation and tuning.

 

Will I learn model evaluation and validation?

 

Yes. Module 6 covers assessment and validation of AutoML-generated models.

 

Does the programme cover deployment?

 

Yes. Module 7 introduces deployment and integration of AutoML models into wider workflows.

 

What certificates are included?

 

The course includes a CPD Accredited PDF Certificate and an Endorsed QLS Certificate in PDF format after successful completion.

 

Is this an Ofqual-regulated Level 5 qualification?

 

CPD accreditation, QLS endorsement and the Level 5 course description should not be treated as evidence of Ofqual-regulated status unless that status is explicitly confirmed for the specific award.

 

Will this course guarantee an AI or machine-learning job?

 

No. The programme supports knowledge development, while employment depends on practical capability, experience, technical skills and employer requirements.

 

What is the difference between this and the free AutoML course?

The free course is Level 3, 200 hours and three modules. This programme is Level 5, 450 hours and eight modules with substantially broader coverage of the AutoML lifecycle.

 

Learning Outcomes
  • Fundamentals of AutoML and its role in machine learning
  • Data preprocessing and feature engineering for AutoML
  • Hyperparameter optimization and tuning
  • Deploying AutoML models in real-world environments
  • Exploring and using popular AutoML platforms
  • Building and training models with AutoML tools
  • Evaluating and validating AutoML models
  • Applying AutoML to industry-specific use cases
Who should learn
this course
  • Data analysts
  • Data scientists
  • AI and ML professionals
  • Software developers
  • Business analysts
  • IT professionals
  • Researchers
  • Students pursuing AI and machine learning careers

SYLLABUS

Module 1

Module 1

Introduction to AutoML and Its Role in Machine Learning

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Module 2

Module 2

Understanding AutoML Platforms

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Module 3

Module 3

Data Preprocessing for AutoML

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Module 4

Module 4

Building and Training Models with AutoML

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Module 5

Module 5

Hyperparameter Optimization and Tuning

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Module 6

Module 6

Model Evaluation and Validation in AutoML

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Module 7

Module 7

Deploying and Integrating AutoML Models

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Module 8

Module 8

Advanced Topics in AutoML for Specific Domains

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Certifications

Certification and Recognition

 

Certification is included with this paid course. After successful completion, you receive a CPD Accredited PDF Certificate and an Endorsed Quality Licence Scheme (QLS) Certificate in PDF format.

These certificates provide evidence that you completed structured study in Automated Machine Learning, including preprocessing, model building, optimisation, validation and deployment. They may be useful as part of a personal learning record or continuing professional development portfolio.

CPD accreditation and QLS endorsement are different from regulated qualification status and from vendor-specific AutoML certification. They should not be presented as equivalent to an Ofqual-regulated qualification or professional licence unless that status is explicitly confirmed for a specific award.

Completing the course does not guarantee employment, promotion, salary progression or professional status. If you need a particular credential for work or further study, check the receiving organisation's requirements before enrolling.

You can review our certificate information and claiming guidance for further details.

Free Introduction or Level 5 AutoML Programme?