MACHINE LEARNING (ML) training courses in the UK
 

Master Machine Learning and Build Intelligent Predictive Solutions

Live, instructor-led, hands-on courses for corporate developers, data analysts and engineers - beginner to advanced - delivered virtually or face to face in London and across the UK.

ML Training • Updated Aug 2026


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Learning Outcomes - What You Will Learn
Core skills and competencies gained across our Machine Learning training programmes.

 

✓ Understand core Machine Learning concepts, including supervised, unsupervised, and deep learning

✓ Build, train, and evaluate ML models using Python, Scikit-learn, and TensorFlow

✓ Apply feature engineering and data preparation techniques for reliable model performance

✓ Develop predictive analytics solutions for real-world business problems

✓ Train and deploy models using Azure Machine Learning and Azure Databricks

✓ Understand neural networks and deep learning fundamentals

✓ Evaluate and tune models to improve accuracy and reliability

✓ Move from notebooks and prototypes to production-ready ML solutions

 

Machine Learning Training for Every Role

Courses matched to your background and what you need to build.

🧑‍💻Software Developers

Build and integrate ML models into applications using Python. Learn the fundamentals of model training, evaluation, and deployment alongside existing development workflows.

🏗️Solutions Architects

Design scalable ML architectures, choose between Azure Machine Learning and Azure Databricks, and define patterns for deploying and operating models in enterprise environments.

📊Data Scientists & ML Engineers

Build deep technical skills in Python, Scikit-learn, TensorFlow, and deep learning. Cover the full pipeline from data preparation and feature engineering through to model deployment.

🏢Business & IT Teams

Understand what Machine Learning can do for your organisation, how predictive analytics works, and where ML fits alongside other AI investments — no coding required.

🔒DevOps & Platform Engineers

Understand how ML models are trained, deployed, and operated at scale, including MLOps considerations for Azure Machine Learning and Databricks environments.

👔Technical Leaders

Understand Machine Learning capabilities, use cases, and technical trade-offs so you can make informed decisions on ML adoption and brief technical teams.

Whether you're beginning your ML journey or looking to advance your technical expertise, this course group provides a complete learning pathway to help you understand how ML works and how to build practical ML applications fit for the enterprise.

What Delegates Say - Testimonials

★★★★★ "A genuinely practical course. We came in with a rough idea of predictive analytics and left with a working model trained on our own data."

Data AnalystInsurance Sector, London

★★★★★ "Excellent depth on feature engineering and model evaluation — areas that are often skipped in other ML courses."

Data ScientistTechnology Sector, London

★★★★★ "The Azure Machine Learning content was directly applicable. We were deploying models to our own environment within days of the course."

ML EngineerPublic Sector, Manchester

 

Training Delivery Options

 

🖥️  Online Live Training

Instructor-led interactive sessions delivered remotely. Same hands-on labs, same expert trainer — no travel required.

📍London Classroom

Attend scheduled public courses at our London training centre. Network with peers from across the industry.

🏢Onsite at Your Premises

We come to you. Ideal for teams of 5+. Content can be customised to your stack, use cases, and objectives.

🎯Bespoke Corporate Programmes

Multi-module Machine Learning programmes designed around your organisation's current capability and target outcomes.

Five core courses: Machine Learning Models with Azure Machine Learning, Machine Learning with Azure Databricks, Python Machine Learning, Intro to AI/ML and Data Science with Python, and Data Science and AI/ML (Python) — covering everything from foundational ML concepts through to production deployment.
It depends on the course. The Python Machine Learning and Intro to AI/ML courses assume some Python familiarity, while the Business & IT track requires no coding at all. The 5-day Data Science and AI/ML course is the most in-depth and technical option.
Software Developers building ML into applications, Solutions Architects designing scalable ML architectures, Data Scientists & ML Engineers wanting deep technical skills, Business & IT Teams evaluating what ML can do (no coding required), DevOps & Platform Engineers handling deployment/MLOps, and Technical Leaders making ML adoption decisions.
Python, Scikit-learn, TensorFlow, Azure Machine Learning, and Azure Databricks — spanning model training, evaluation, feature engineering, deep learning fundamentals, and production deployment.
Azure Machine Learning focuses on training, tuning, and deploying custom ML models (e.g. classification, regression). Azure Databricks is built for large-scale data engineering and ML workloads within a Lakehouse architecture. The course content specifically helps clarify when to choose each for your architecture.
Yes — delegates build and train models on their own data during the course. Feedback specifically highlights leaving with "a working model trained on our own data" and being able to deploy to their own Azure environment within days.
Four ways: Online Live Training (instructor-led, remote), London Classroom (in-person), Onsite at Your Premises (for teams of 5+), or Bespoke Corporate Programmes built around your organisation's current capability and target outcomes.
Yes — the courses cover moving from notebooks/prototypes to production-ready ML solutions, including MLOps considerations for Azure Machine Learning and Databricks environments, aimed specifically at DevOps and Platform Engineers.
Yes — onsite delivery is available for teams of 5+, and bespoke multi-module Machine Learning programmes can be designed around your organisation's current capability level and target outcomes.

CONTACT


+44 (0)20 8446 7555

enquiries@jbinternational.co.uk

 

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