Skip to main content
FORWARD
University
Under review

Master of Science in Human-Centred AI Systems

Most intelligent systems fail not because the model was wrong but because the system ignored the people who had to use it, trust it or live with its decisions. Human centred design, human computer interaction, and the study of how people and intelligent systems actually work together have become ...

MScHybrid12 months (2 semesters)Intake August 202760 credit units

Employment thesis

What this programme is designed to produce

Forward publishes the destination of every programme before you enrol. If the thesis stops holding, the programme is reviewed and, where necessary, retired. Next review: 2031.

Roles

  • Human centred AI designer
  • AI product designer
  • user experience researcher for intelligent systems
  • responsible AI specialist
  • human computer interaction researcher
  • product manager for AI
  • AI adoption and change lead
  • design researcher

Employer types

  • Regional and global technology firms
  • banks
  • insurers and mobile money operators
  • health and agricultural technology firms
  • government digital and public service agencies
  • international development and humanitarian organisations
  • design and consulting firms
  • research institutes
  • the graduate's own venture, incubated through the Forward Venture Studio

Target outcomes we hold ourselves to

  • This programme is built for designers, researchers, product professionals and engineers moving into human centred roles for intelligent systems, and supports remote employment at international rates. Progression routes include doctoral study in technology, policy and society.

Compulsory · The Forward Core

How the Core works →

Every Forward programme, including this one, carries the same five cross-cutting requirements. They are graded, not optional.

  • AI Fluency
  • Quantitative Reasoning
  • Ethics and African Context
  • Human-Advantage Skills
  • Enterprise

Includes 12 months paid work-integrated learning

Postgraduate programmes carry work integrated learning inside the taught structure rather than the twelve month undergraduate cooperative education placement. Read the co-op commitment

Am I eligible?

Check yourself against the published requirements

7 questions written specifically for Master of Science in Human-Centred AI Systems. Every answer is checked against a requirement Forward has published, and the result tells you which page that requirement comes from. Indicative only, the admissions office decides on your full file.

Question 1 of 70%

What is the highest qualification you hold?

Requirement tested: A completed bachelor's degree in a cognate field, or a recognised equivalent with professional experience.

Curriculum structure

The same degree, in both pathways

Every Forward programme is published in both pathways: Path One, the term plan of two six-month terms, and Path Two, the block sequence of twelve four-week blocks. Same competencies, same assessments, same award. Toggle to see this programme in each.

Path One term plan shown

Path One · The Term Model

SEMESTER 1 | YEAR 1 | 25 COMPETENCY UNITSYear 1
25 credit units
CodeCourseCUHours
FDC 501
Applied Intelligence for Professionals
Both
42-2-0
FDC 502
Research Evidence and Method
Both
42-2-0
MHCA 510
Human Computer Interaction for Intelligent Systems
Both
63-2-2
MHCA 511
Design Research Methods
Performance
63-2-4
MHCA 512
Trust, Explanation and Human AI Interaction
Both
53-2-2
SEMESTER 2 | YEAR 1 | 35 COMPETENCY UNITSYear 1
35 credit units
CodeCourseCUHours
FDC 503
Governance, Ethics and Leadership of Intelligent Systems
Both
42-2-0
MHCA 520
Responsible AI, Fairness and Accountability
Performance
52-2-4
MHCA 521
Prototyping Intelligent Interfaces
Both
42-2-2
MHCA 522
Measuring Human Outcomes and System Impact
Performance
42-2-4
MHCA 523
Adoption, Change and the Sociotechnical System
Objective
32-2-0
MHCA 530
Human-Centred AI Project
Performance
150-2-12

Total credit units: 60

Curriculum source

Forward University Curriculum Compendium

Assessment

Coursework + project + integrated exam

Work-integrated learning

12 months paid co-operative education

Your week at Forward

A typical week on Master of Science in Human-Centred AI Systems

Path One, the Term Model: your own pace across a six-month term, one live session a week, short flexible lessons, and assessment on demand.

Monday

Tuesday

Wednesday

Thursday

Friday

Mandatory live session Flexible bite-sized lesson Optional event

Curriculum explorer

Drill into the degree, step by step

Choose a study path, then a year, then a term or block, then a course. Credit totals add up as you go, and every course shows what comes before it and what it unlocks.

Step 1, choose a year

Step 2, choose a term

SEMESTER 1 | YEAR 1 | 25 COMPETENCY UNITS

Year 1 · this step is worth 25 CU

Cumulative

25

Programme total

60

25 CU of 60 CU completed by the end of this step (42%)

Step 3, choose a course

Pick a course to see the detail

Credits, assessment, prerequisites and what each course unlocks later.

The twelve Forward capabilities

What this programme develops in you

Every Forward degree develops the same twelve cross-cutting capabilities. The profile below is the level this programme is designed to develop and verify by graduation, on the four-level scale in Part B2 of the Curriculum Compendium. Every claim above Level 2 is verified by someone other than the teaching lecturer.

  • C1Intelligent Systems FluencyLevel 3 of 4, Independent
  • C2Quantitative and Evidential ReasoningLevel 3 of 4, Independent
  • C3Ethical and Contextual Judgement CriticalLevel 4 of 4, Leading
  • C4Communication and Persuasion CriticalLevel 4 of 4, Leading
  • C5Disciplinary MasteryLevel 3 of 4, Independent
  • C6Technical Production and CraftLevel 3 of 4, Independent
  • C7Problem Framing and Systems Thinking CriticalLevel 4 of 4, Leading
  • C8Collaboration and Multidisciplinary Teaming CriticalLevel 4 of 4, Leading
  • C9Enterprise, Value and Commercial LiteracyLevel 3 of 4, Independent
  • C10Professional Conduct and Workplace PerformanceLevel 3 of 4, Independent
  • C11Learning to Learn and Adaptive CapacityLevel 3 of 4, Independent
  • C12Stewardship and Public ContributionLevel 4 of 4, Leading

Critical capabilities for this programme: Ethical and Contextual Judgement · Communication and Persuasion · Problem Framing and Systems Thinking · Collaboration and Multidisciplinary Teaming. A graduate cannot pass out of this programme below the stated level on any capability marked critical.

Programme Learning Outcomes

What you will be able to do

Each outcome is assessed, and each is tagged with the Forward capabilities it is verified against.

  1. PLO 1Study how people actually work with an intelligent system, using valid qualitative and quantitative methods, and turn the findings into design decisions.
  2. PLO 2Design the interaction between a person and an intelligent system so that it is usable, understandable and appropriately trusted.
  3. PLO 3Measure trust, reliance and the human outcomes of a deployed system, including its failures and harms.
  4. PLO 4Apply responsible AI and fairness reasoning to a concrete system and hold it accountable to the people it affects.
  5. PLO 5Explain an intelligent system's behaviour and limits to the audience that must act on it.
  6. PLO 6Work as the human centred member of a multidisciplinary team, translating between the model, the design and the affected people.
  7. PLO 7Evaluate an intelligent system against human centred criteria and recommend deployment, redesign or refusal.
  8. PLO 8Deliver a human centred AI project for an external host with a measured outcome.
  9. PLO 9Cost and defend a human centred design decision to a commercial and an affected audience.
  10. PLO 10Acquire and demonstrate a new capability without formal instruction, evidenced in the Capability Passport.

Why this programme exists

Most intelligent systems fail not because the model was wrong but because the system ignored the people who had to use it, trust it or live with its decisions. Human centred design, human computer interaction, and the study of how people and intelligent systems actually work together have become standard functions in the organisations deploying AI, and there is almost no local capacity to staff them. This programme builds the specialist who sits between the model and the human: designing the interaction, studying the use, measuring the trust, and holding the system accountable to the people it affects. It is a taught, project heavy conversion for designers, social scientists, product people and engineers moving toward this fast forming discipline.

Admission requirements

A good first degree (second class or above) in design, a social science, computing, engineering, psychology or a cognate field; or another first degree with demonstrated relevant practice; plus a portfolio or short design and reasoning task at admission scored against Capabilities C4 and C7. Substantial professional experience is admitted through recognition of prior learning against the same profile. All applicants must demonstrate competence in English, the language of instruction, through their qualifications or an approved proficiency test under Part A. International and non standard qualifications are assessed for equivalence against the profile above under the Credential Portability provisions, so that a suitably prepared applicant may enter from anywhere in the world. Selection considers the whole application, including the structured admission task, and is conducted without discrimination under the University's admissions policy. Alternative pathways: recognition of prior learning against the admission profile under Part G, including substantial professional practice in lieu of the named first degree field. Online components require the Digital Readiness orientation under Part D6.

AI & Computing

Other open programmes in this School

BSc (Hons)

Bachelor of Science in Artificial Intelligence

Artificial intelligence and big data is the fastest growing skill category in the world, two thirds of employers intend to hire specifically for it, and the measured wage premium for demonstrable AI capability now exceeds sixty per cent of ...

View programme
BSc (Hons)

Bachelor of Science in Data Science and Analytics

Every institution in Uganda now holds more data than it can interpret, and almost none of them can convert it into a decision. The gap is not modelling talent; it is the far scarcer ability to move from a messy administrative dataset to a d...

View programme
BSc (Hons)

Bachelor of Science in Software Engineering with Intelligent Systems

The largest addressable domestic technology market in Uganda is software, and the largest single complaint from employers is that graduates can pass an algorithms examination but have never shipped anything to a user, never operated a syste...

View programme
BSc (Hons)

Bachelor of Science in Cybersecurity and Digital Trust

Uganda is digitising public services, payments and identity faster than it is producing people qualified to defend them, and the shortage is acute at exactly the level — hands on defensive operations — where the region's degree programmes a...

View programme
BSc (Hons)

Bachelor of Science in Computer Science with Advanced and Quantum Computing

Every serious technology economy needs a small number of people who understand computation deeply enough to build the layer everyone else stands on: compilers, runtimes, schedulers, numerical kernels, cryptographic primitives and, increasin...

View programme
MSc

Master of Science in Machine Learning and Foundation Models

A research intensive degree for the small number of people who will build, adapt and evaluate frontier-class models on and for the continent. It exists because Africa is acquiring accelerated computing faster than it is acquiring the people...

View programme
MSc

Master of Science in Applied Artificial Intelligence

A practitioner conversion degree for working professionals — clinicians, bankers, engineers, agronomists, civil servants, teachers, lawyers — who need to build and govern intelligent systems in their own sector rather than become research s...

View programme
MSc

Master of Science in Data Engineering and Cloud Architecture

Every organisation that wants intelligent systems discovers first that it cannot get to its own data. Data engineering is the least glamorous and most binding constraint on African AI adoption, and it is almost entirely untaught at postgrad...

View programme
MSc

Master of Science in Cybersecurity and Digital Forensics

Uganda's critical financial, identity and public service infrastructure is now digital, and the national capacity to investigate, attribute and defend against attacks on it is thin. This programme builds senior defenders, investigators and ...

View programme
PhD

Doctor of Philosophy in Artificial Intelligence

Africa cannot import its way to research capacity. This doctorate is designed to produce researchers who will stay, supervise, and build institutions, and it therefore carries two requirements unusual in the region: every candidate must pub...

View programme
BSc (Hons)

Bachelor of Science in Computing Infrastructure and Cloud Systems

Every organisation that wants intelligent systems, digital services or reliable operations discovers the same binding constraint: it cannot build or run the infrastructure underneath them. Cloud architecture, systems engineering, networks and site reliability are the least glamorous and most ...

View programme
BSc (Hons)

Bachelor of Science in Cybersecurity Operations and Infrastructure Defence

Uganda is digitising public services, payments and identity faster than it is producing people who can defend the infrastructure underneath them, and the shortage is most acute not in policy but in hands on defensive operations: the engineers who harden a network, run a security operations centre, ...

View programme
MSc

Master of Science in Applied Machine Learning

There is a large and growing population of technically capable professionals in the region who can program and reason quantitatively but who cannot yet build, evaluate and deploy machine learning systems to a professional standard. They do not need a research degree; they need a rigorous, build ...

View programme