Data Science Training for Earth Sciences

Master Data Science and Analytics for Water, Environment
& Climate Research

Practical, live training in R, statistics, and spatial analysis — built specifically for hydrologists, environmental scientists, and climate researchers.

Explore Courses → Meet the Instructor
6+ Live Courses
Live Interactive Sessions
Real Hydrological Datasets
∞ Recording Access

Tools you will learn

R R
RStudio RStudio
QGIS QGIS
GEE Earth Engine
Python Python
Upcoming Live Courses
Practical Training for
Environmental Professionals

Every course uses real hydrological and environmental datasets — no generic CSV examples.

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R · Hydrology
R for Hydrologists & Water Resources Researchers
Data import, dplyr wrangling, ggplot2 visualisation, and time series analysis — all using real streamflow and groundwater data.
$0 $0 Coming Soon
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R · Environment
R for Environmental Data Analysis
Air quality, water quality, biodiversity indices, and pollution data — analysed and visualised in R from scratch.
$0 New
🌾
R · Agriculture
Spatial Data Analysis for Agriculture & Land Use
NDVI, crop monitoring, soil data, and land use change analysis using R, sf, and Google Earth Engine.
$0 Coming Soon
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R · Climate
Climate Data Analysis with R
ERA5, CHIRPS, ENSO indices, trend analysis, and climate risk modelling — practical tools for climate researchers.
$0 Coming Soon
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R · Spatial
Spatial Analysis & Map Making in R
sf, mapview, ggplot2 maps, coordinate systems, and spatial joins — from shapefile to publication-quality map.
$0 Coming Soon
📊
R · Statistics
Extreme Value Theory for Flood Frequency Analysis
GEV, GPD, L-moments, return periods, and nonstationary models — EVT made accessible for practising hydrologists.
$0 Coming Soon
Why HydroData Academy
Built for Earth Scientists,
Not General Audiences
🔴
Live & Interactive
Real-time sessions where you run code, ask questions, and solve problems — not pre-recorded lectures watched passively.
🌊
Domain-Specific Datasets
Every exercise uses streamflow, groundwater, rainfall, climate indices, or satellite data — not generic spreadsheets.
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Instructor with Field Experience
Taught by an active PhD researcher in Hydroinformatics and AI — someone who uses these tools daily in research.
⏱️
Lifetime Recording Access
All sessions recorded and shared via Google Drive. Revisit any concept at any time, forever.
📜
Completion Certificate
Receive an e-certificate upon completing the course — shareable on LinkedIn and academic profiles.
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Small Cohorts
Limited seats per session to ensure every participant gets direct attention and personalised feedback.
Who Is This For
These courses are designed for you
if you work in…
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Hydrology
Flood analysis, groundwater, streamflow modelling
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Environmental Science
Air/water quality, pollution, ecosystem analysis
🌾
Agriculture
Crop monitoring, soil data, irrigation planning
🌡️
Climate Research
Trend analysis, climate indices, risk modelling
🗺️
GIS & Remote Sensing
Spatial analysis, satellite data, land use change
💼 🎓 ▶️ 🔬
Meet the Instructor
Murtada Khalafalla Ibrahim
PhD Candidate in Artificial Intelligence · Hydroinformatics & Climate Risk Researcher
Data & AI Governance Consultant · Universiti Teknologi Malaysia (UTM)

With over 15 years in Data & AI Governance and active PhD research in Extreme Value Theory, Explainable AI (XAI), and Nonstationary Flood Frequency Analysis at UTM Malaysia — I bring both institutional experience and cutting-edge research methodology to every training session.

My research focuses on Hydroinformatics, Environmental Data Science, Climate Risk Modelling, and Explainable AI applied to tropical data-scarce river basins. Every course I design draws directly from this research and from real challenges faced by environmental professionals. AI-driven solutions for Environmental Data, Climate Risk, and Sustainable Decision-Making.

CDMP® TOGAF® PRINCE2® COBIT® ITIL® ISO 27001 ISO 31000 PhD Candidate @ UTM
Common Questions
FAQ
Select your preferred course and click Register. Complete the registration form and payment to secure your place. You will receive all session details and access links by email within 24 hours.
No prior R or Python experience is required for introductory courses. You need a working computer and familiarity with your own field's data — streamflow, environmental measurements, climate indices, etc.
Most courses run as intensive 1–5 day programmes. The exact schedule is listed under each course. Recorded sessions are always provided so you can revisit content at your own pace.
Yes. Upon successful completion you receive an e-certificate from HydroData Academy, which you can add to your LinkedIn profile and academic CV.
Yes. All participants receive lifetime access to recorded sessions shared via Google Drive. Revisit any lesson at any time for revision or continued learning — no expiry.
Course fees are generally non-refundable. Refunds are only considered when a session is cancelled by the instructor, in which case a full refund or rescheduling option is provided.
Get In Touch

Ready to upskill your research workflow?

Join the next live cohort or send a message to discuss institutional group training.

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