Master of Science in Precision Agriculture
Farming is becoming a data and technology discipline, with sensing, robotics, remote sensing and machine learning turning agriculture into something that can be measured and optimised field by field. The region is acquiring the technology faster than the people who can make it pay in African ...
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
- Precision agriculture specialist
- agricultural data scientist
- agtech systems engineer
- remote sensing and geospatial specialist
- digital agronomy lead
- farm technology manager
- agricultural robotics specialist
- technical founder
Employer types
- Agtech and precision agriculture firms
- large farms and plantations
- agricultural input and equipment firms
- development and research organisations
- government agriculture agencies
- agricultural finance and insurance firms
- cooperatives and aggregators
- research institutes
- the graduate's own venture, incubated through the Forward Venture Studio
Target outcomes we hold ourselves to
- This programme is built for agronomists, engineers, data scientists and agricultural professionals moving into precision agriculture, and supports senior technical roles and ventures. Progression routes include doctoral study.
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 Precision Agriculture. 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.
What is the highest qualification you hold?
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
| Code | Course | CU | Hours |
|---|---|---|---|
| FDC 501 | Applied Intelligence for Professionals Both | 4 | 2-2-0 |
| FDC 502 | Research Evidence and Method Both | 4 | 2-2-0 |
| MPAG 510 | Foundations of Precision Agriculture Both | 6 | 3-2-2 |
| MPAG 511 | Agricultural Sensing, Data and Connectivity Performance | 6 | 3-2-4 |
| MPAG 512 | Remote Sensing and Geospatial Analysis for Agriculture Both | 5 | 3-2-2 |
| MPAG 513 | Machine Learning for Agriculture Both | 5 | 3-2-2 |
| Code | Course | CU | Hours |
|---|---|---|---|
| FDC 503 | Governance, Ethics and Leadership of Intelligent Systems Both | 4 | 2-2-0 |
| MPAG 520 | Agricultural Robotics and Automation Performance | 7 | 3-2-4 |
| MPAG 521 | Digital Agronomy and Decision Systems Both | 5 | 3-2-2 |
| MPAG 522 | Economics and Adoption of Agricultural Technology Performance | 5 | 2-2-4 |
| MPAG 523 | Advanced Precision Agriculture Elective Performance | 5 | 2-2-4 |
| MPAG 524 | Agtech Systems Elective Objective | 4 | 3-2-0 |
| Code | Course | CU | Hours |
|---|---|---|---|
| MPAG 530 | Precision Agriculture Project and Dissertation Performance | 20 | 0-2-12 |
| MPAG 531 | Doctoral and Research Preparation Seminar Objective | 5 | 3-2-0 |
| MPAG 532 | Research Translation and Commercialisation Objective | 5 | 3-2-0 |
Total credit units: 90
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 Precision Agriculture
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
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 | 30 COMPETENCY UNITS
Year 1 · this step is worth 30 CU
Cumulative
30
Programme total
90
30 CU of 90 CU completed by the end of this step (33%)
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 Fluency CriticalLevel 4 of 4, Leading
- C2Quantitative and Evidential Reasoning CriticalLevel 4 of 4, Leading
- C3Ethical and Contextual JudgementLevel 3 of 4, Independent
- C4Communication and PersuasionLevel 3 of 4, Independent
- C5Disciplinary MasteryLevel 4 of 4, Leading
- C6Technical Production and Craft CriticalLevel 4 of 4, Leading
- C7Problem Framing and Systems Thinking CriticalLevel 4 of 4, Leading
- C8Collaboration and Multidisciplinary TeamingLevel 3 of 4, Independent
- C9Enterprise, Value and Commercial LiteracyLevel 3 of 4, Independent
- C10Professional Conduct and Workplace PerformanceLevel 3 of 4, Independent
- C11Learning to Learn and Adaptive CapacityLevel 4 of 4, Leading
- C12Stewardship and Public ContributionLevel 4 of 4, Leading
Critical capabilities for this programme: Intelligent Systems Fluency · Quantitative and Evidential Reasoning · Technical Production and Craft · Problem Framing and Systems Thinking. 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.
- PLO 1Design a precision agriculture system for a real farming context and justify it against simpler alternatives.
- PLO 2Engineer agricultural sensing, data and connectivity under real constraints.
- PLO 3Apply remote sensing and geospatial analysis to an agricultural decision.
- PLO 4Build and evaluate machine learning models on agricultural data honestly.
- PLO 5Integrate robotics and automation into an agricultural operation.
- PLO 6Turn precision data into an agronomic decision a farmer will act on.
- PLO 7Assess the economics of a precision intervention for a real farm.
- PLO 8Deliver a major precision C6, C8 agriculture project on real farms with a measured outcome.
- PLO 9Communicate and C3, C7 defend a precision agriculture recommendation to farmers and investors.
- PLO 10Acquire and demonstrate C10 a new capability without formal instruction, evidenced in the Capability Passport.
Why this programme exists
Farming is becoming a data and technology discipline, with sensing, robotics, remote sensing and machine learning turning agriculture into something that can be measured and optimised field by field. The region is acquiring the technology faster than the people who can make it pay in African conditions of small farms, mixed cropping and thin data. This masters builds the specialist who can design and deploy precision agriculture that works here, and it terminates in a major applied project delivered on real farms or in a real agricultural operation, weighted toward deployable systems rather than simulation.
Admission requirements
A good first degree (second class or above) in agriculture, engineering, a science, computing or a cognate field; or substantial relevant experience admitted through recognition of prior learning; plus a short technical task scored against Capabilities C2 and C6. 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.
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