Information and Booking

Trainer: Corndel and Imperial College Executive & Professional Education
Cost: The course fee of £22,000 is fully funded by Imperial’s Growth and Skills Levy, and there is no cost to the individual or department. The standard cancellation policy will apply.
Duration: 22 months
Starts: Launches on Monday 19 April 2027, various groups online
Book your place on the briefing session on Thursday 11 February 2027, 10.00 – 11.00  

Email us if you have any questions or queries.

Overview

Applied AI Engineering is one of four new AI Academy programmes designed to equip staff with the technical skills and confidence to use Artificial Intelligence. This in-depth programme is for data and technology professionals with a good foundational knowledge who wish to deepen their AI expertise and become Machine Learning solution experts. Delivered over 22 months, it will allow you to take full ownership of end-to-end systems, including design, build, deployment and validation of machine learning and/or artificial intelligence solutions. Key themes include:

  • Scoping, prototyping and evidencing Machine Learning services
  • Programming, including coding with Python
  • Data literacy and Maths for Machine Learning Engineers
  • Designing, training and debugging neural networks
  • Optimising Machine Learning models

Delivery will include 16 full-day, live virtual workshops led by coaches with real-world experience in building and deploying Machine Learning and AI and working with the CRISP-ML(Q) framework. Learners will also attend monthly 1-1 sessions with a specialist coach, undertake guided self-learning, and bite-sized practical projects. The learning is complemented by a special masterclass programme delivered by Imperial academics on themes such as Scaling Generative AI and Digital Transformation. As such, this course is a unique opportunity to access leading-edge thinking in Artificial Intelligence and technology.

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Who should attend

The programme is geared primarily at data and digital technology professionals who wish to deepen their AI expertise and become Machine Learning solution experts. Most learners will work in data-focused roles (e.g. Data Analyst, Data Scientist, Business Intelligence, Database Administrator, Data Engineer) or have digital technology specialisms (e.g. DevOps, Software Engineer, Solutions Engineer, Cloud Solution Architect).

Above all, you need to be in a work role where you have the time, tools and data to design, build, deploy and validate Machine Learning and/or Artificial Intelligence solutions. As this is a level 6 (degree-level) programme, learners should be committed to undertaking in-depth technical learning across data, programming and statistics.

Corndel will assess suitability during the application process to ensure that learners are in roles where they can apply the learning, meet learning outcomes and fully maximise the value of this programme.

Eligibility

Applicants should:

  • Be working in a data or digital technology role and have scope to design, build, deploy and validate Machine Learning and/or Artificial Intelligence solutions. Corndel will assess the suitability of your work role during the application process.
  • Be committed to learning about Artificial Intelligence and Machine Learning in a detailed way to include programming (Python) and using Cloud technologies (e.g. AWS, Azure). Some prior programming experience (Python or other languages) is useful, but not mandatory; more important is a willingness to challenge yourself and develop with coding in Python.
  • Have a GCSE (or equivalent) pass in Maths and English.
  • Have either: an A-level (or equivalent) pass in a STEM subject (e.g., a Science, Maths, Computing) or a level 4 Apprenticeship in a technical subject (e.g., Software Engineer, DevOps Engineer, Data Analyst) or 2+ years' experience in a technical role (one that has exposure to programming or data analysis, or similar) or a demonstrable passion for data/coding/programming with sample projects completed.
  • Have approval from your line manager to participate.
  • Be ready to commit to the minimum learning requirement (approximately one day per week) and discuss with your manager how this can be balanced with operational demands.
  • Have enough time remaining on your contract of employment to complete the programme in full (at least 22 months from the course start date).
  • Have the right to work in the UK for the full duration of your programme and an eligible residency status (please refer to Annex A: Residency Eligibility Criteria in the Apprenticeship Funding Rules for further information).
  • Not currently be receiving any other direct/indirect funding from the Department for Education (e.g. student finance).
Course content

The programme is fully aligned to the Level 6 Machine Learning Engineer apprenticeship standard, and the course will incorporate units on: 

  • How AI changes our world
  • Immediate impact with Machine Learning
  • Programming for intelligent products
  • Machine-Learning data environments
  • MLOps and Production
  • Essential Maths for ML Engineers
  • Supervised Machine Learning
  • Feature engineering and testing
  • How machines learn – unsupervised, ensemble & reinforcement
  • Neural networks for deep learning
  • ML optimisation techniques and strategies
  • Solving big business problems with AI
  • LLMs and GenAI deployments
  • Thinking inside the box – explainable AI
  • Into the future – project work and innovation

View the curriculum on the Corndel website

Successful completion

On successful completion, participants will gain a Level 6 Machine Learning Engineer apprenticeship, a nationally recognised qualification.

You will also become an Associate Alumnus of Imperial and have access to a range of alumni benefits.