A study-guide imprint for AI and machine learning
Exam companions for university modules in AI, machine learning, large language models and transformer architectures. Written by practitioners. Current enough to trust. Rigorous enough to earn the grade.
For students chasing the top of the mark scheme, and the module leaders and librarians who stock their shelves.
What it is
Full Marks Press publishes exam companions for university modules in AI, machine learning, large language models and transformer architectures.
Each guide is written by practitioners who build, train and evaluate these systems professionally, pitched at both undergraduate and postgraduate level, and revised on a published schedule so the content tracks the syllabus as taught now.
Responsible AI is treated as core course material. Bias, evaluation limits, safety and governance appear inside the relevant technical chapters, because that is where examiners increasingly put them and where practitioners actually encounter them.
The guides
AI modules move faster than traditional textbooks. Every title states its edition date and syllabus year on the cover, and the catalogue is built to keep pace.
Bias and fairness, accountability and governance, privacy and safety, and the regulation shaping how AI is built and used, with the arguments and worked examples a strong exam answer needs.
Supervised and unsupervised learning, bias and variance, model evaluation, trees and ensembles, and the mathematics the mark scheme actually rewards.
Free review copies
Students and staff can claim a free advance copy of any live guide. Read it, and if it earns it, an honest review helps the next student find it.
Get a free guideWhy it is different
Our authors build, train and evaluate these systems professionally. The guides reflect how the technology actually behaves, and flag where the lecture-slide simplification will cost marks at postgraduate level.
We name the architectures, papers and techniques that matter this academic year, and we date our claims. Where the field is unsettled, we say so and cite accordingly.
Bias, evaluation limits, safety and governance sit inside the relevant technical chapters, not in a final-chapter sidebar. That is where the marks are moving.
Ahead of the reading list
For students, module leaders and academic librarians. Pick a guide and we send the full ebook to your inbox, free. Read it, and if it helps, an honest review helps the next student. No spam, unsubscribe any time.
Full Marks Press, a Verity AI imprint. About the imprint.
Read a free sample
Every guide carries a free sample on Amazon: read the opening and mark it yourself. If it does not read like the sharpest teaching assistant on the module, do not buy it. Students, module leaders and librarians all welcome.
Browse the guides