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FORWARD
University
Under review

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 ...

MScHybrid18 months (3 semesters)Intake August 202790 credit units

The four facts

What you actually need to compare

Award and entry
MSc
A
Duration and mode
18 months (3 semesters)
Hybrid. Includes 12 months of paid, assessed cooperative education.
Cost
UGX 3,600,000 per year
Tier 2 laboratory classification. Includes UGX 600,000 annual laboratory premium.
Outcome targeted
Climate data scientist, agricultural risk modeller, catastrophe and insurance analyst
Reviewed by 2031. If the thesis stops holding, the programme is reviewed.
Fee structure Key dates 90 credit units

Pricing Model 5.1 · The Forward Standard

Master of Science in Climate Data Science fee

UGX 3,600,000 per year

Laboratory tier
Tier 2
Annual premium
UGX 600,000
Per semester
UGX 1,800,000
Whole programme
UGX 5,400,000
Approximate USD
≈ USD 1,421

What this fee includes

  • Teaching, practice tutoring, assessment and competency verification
  • The Amagezi platform and AI tutor around the clock
  • All learning materials
  • Every examination, including first resits
  • Identity card, library, guild, sports and basic wellbeing
  • Co-op placement matching and the Capability Passport
  • Graduation and the statutory NCHE fee
  • Online application

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

Read the co-op commitment

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.

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

TERM 1 (SIX MONTHS) | FORMERLY SEMESTER 1Year 1
30 credit units
CodeCourseCUHours
FDC 501
Applied Intelligence for Professionals
Both
42-2-0
FDC 502
Research Evidence and Method
Both
42-2-0
ECE 510
Climate Science and Model Output Interpretation
Both
64-2-2
ECE 511
Machine Learning for Environmental Data
Performance
63-2-4
ECE 512
Big Geospatial and Climate Data Engineering
Performance
52-2-4
ECE 513
Statistics of Extremes and Uncertainty
Both
53-2-2
TERM 2 (SIX MONTHS) | FORMERLY SEMESTER 2Year 1
27 credit units
CodeCourseCUHours
FDC 503
Governance, Ethics and Leadership of Intelligent Systems
Both
42-2-0
ECE 520
Downscaling, Bias Correction and Forecast Verification
Performance
74-2-4
ECE 521
Agricultural and Hydrological Modelling
Performance
63-2-4
ECE 522
Catastrophe Risk and Index Insurance Design
Both
53-2-2
ECE 523
Climate Services and User Centred Design
Both
53-2-2
TERM 3 (SIX MONTHS) | FORMERLY SEMESTER 3:Year 2
30 credit units
CodeCourseCUHours
ECE 530
Dissertation: Applied Climate Data Product (client verified)
Performance
200-2-38
ECE 531
Early Warning Systems Practicum
Performance
51-0-8
ECE 532
Research Communication and Publication
Objective
54-2-0

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

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

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.

  1. PLO 1Process and analyse large climate, satellite and reanalysis datasets.
  2. PLO 2Apply statistical and machine learning downscaling and bias correction methods.
  3. PLO 3Build predictive systems for agricultural, hydrological and disaster risk applications.
  4. PLO 4Quantify and communicate forecast uncertainty and skill honestly.
  5. PLO 5Design a climate service that a specific user will actually use.
  6. 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.