Written by practitioners
Our authors build, train and evaluate these systems professionally. The guides reflect how the technology actually behaves, and they flag where lecture-slide simplifications will cost marks at postgraduate level.
Exam companions for AI and machine learning
Full Marks Press
Aim for full marks.
Practitioner-written exam companions for university modules in AI, machine learning, large language models and transformer architectures, current enough to trust and rigorous enough to earn the grade. Written for undergraduates and postgraduates who want the top of the mark scheme.
Get in touchWhat we offer
Study guides built to the standard of the best student on the course, typeset by a proper publisher. Every claim is dated, every source cited.
Current by design
AI modules move faster than traditional textbooks. Each guide states its edition date, tracks the syllabus as taught now, and is revised on a published schedule.
Responsible AI as course material
Bias, evaluation limits, safety and governance sit inside the relevant technical chapters, because that is where examiners increasingly put them and where practitioners meet them.
Who it is for
One standard, pitched to readers who want the mark scheme in full, whatever their level.
Undergraduates
- Sitting AI and machine learning modules and aiming beyond a pass.
- Worked examples with the marking logic made explicit.
- Diagrams simple enough to redraw from memory in an exam.
Postgraduates
- Working on transformers, large language models and evaluation.
- Precise naming of real architectures, papers and techniques.
- Notes on where the field is unsettled, cited accordingly.
Module leaders and libraries
- Reading lists that need a current, dated companion.
- Editorial standards you can stock with confidence.
- Responsible AI covered throughout, not bolted on.