Master of Science in Climate Data Science
Climate models produced for the world are too coarse to tell a Ugandan district when to plant, a bank whether to lend, or an insurer what to charge. Closing that resolution gap requires machine learning applied to climate, agricultural and ...
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
- Climate data scientist
- agricultural risk modeller
- catastrophe and insurance analyst
- early warning systems specialist
- research scientist
- climate service designer.
Employer types
- Meteorological and hydrological services
- insurers and reinsurers
- agricultural finance
- humanitarian and early warning agencies
- research institutes
- and climate funds.
Target outcomes we hold ourselves to
- A scarce, technically demanding specialisation with international research and commercial demand.
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
Am I eligible?
Check yourself against the published requirements
7 questions written specifically for Master of Science in Climate Data Science. 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 |
| ECE 510 | Climate Science and Model Output Interpretation Both | 6 | 4-2-2 |
| ECE 511 | Machine Learning for Environmental Data Performance | 6 | 3-2-4 |
| ECE 512 | Big Geospatial and Climate Data Engineering Performance | 5 | 2-2-4 |
| ECE 513 | Statistics of Extremes and Uncertainty Both | 5 | 3-2-2 |
| Code | Course | CU | Hours |
|---|---|---|---|
| FDC 503 | Governance, Ethics and Leadership of Intelligent Systems Both | 4 | 2-2-0 |
| ECE 520 | Downscaling, Bias Correction and Forecast Verification Performance | 7 | 4-2-4 |
| ECE 521 | Agricultural and Hydrological Modelling Performance | 6 | 3-2-4 |
| ECE 522 | Catastrophe Risk and Index Insurance Design Both | 5 | 3-2-2 |
| ECE 523 | Climate Services and User Centred Design Both | 5 | 3-2-2 |
| Code | Course | CU | Hours |
|---|---|---|---|
| ECE 530 | Dissertation: Applied Climate Data Product (client verified) Performance | 20 | 0-2-38 |
| ECE 531 | Early Warning Systems Practicum Performance | 5 | 1-0-8 |
| ECE 532 | Research Communication and Publication Objective | 5 | 4-2-0 |
Total credit units: 87
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 Climate Data Science
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
TERM 1 (SIX MONTHS) | FORMERLY SEMESTER 1
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 4 of 4, Leading
- C5Disciplinary MasteryLevel 4 of 4, Leading
- C6Technical Production and CraftLevel 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 4 of 4, Leading
- C11Learning to Learn and Adaptive CapacityLevel 4 of 4, Leading
- C12Stewardship and Public Contribution CriticalLevel 3 of 4, Independent
Critical capabilities for this programme: Intelligent Systems Fluency · Quantitative and Evidential Reasoning · Problem Framing and Systems Thinking · Stewardship and Public Contribution. 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 1Process and analyse large climate, satellite and reanalysis datasets.
- PLO 2Apply statistical and machine learning downscaling and bias correction methods.
- PLO 3Build predictive systems for agricultural, hydrological and disaster risk applications.
- PLO 4Quantify and communicate forecast uncertainty and skill honestly.
- PLO 5Design a climate service that a specific user will actually use.
- PLO 6Conduct and report original applied research.
Why this programme exists
Climate models produced for the world are too coarse to tell a Ugandan district when to plant, a bank whether to lend, or an insurer what to charge. Closing that resolution gap requires machine learning applied to climate, agricultural and ...
Admission requirements
A Bachelor's degree of at least Second Class Lower Division in a quantitative discipline with demonstrated programming ability. Alternative pathways: Foundation Year, diploma entry with advanced standing, mature age entry and recognition of prior learning, all governed by Part A5 and Part G. Online applicants additionally complete the compulsory Digital Readiness orientation under Part D6.
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