The New Frontier of Geospatial Science

A comprehensive learning pathway to master cloud-native environmental science, from foundational concepts to advanced AI forecasting.

The Old Workflow: A "Time-to-Science" Bottleneck

Traditional geospatial research involves a linear, time-consuming process that creates significant delays between data acquisition and actionable insight.

1. Discover

Manually search disparate data portals.

→
2. Download

Wait hours or days for large files.

→
3. Process

Spend weeks cleaning and preparing data.

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4. Analyze

Run computations on local machines.

→
5. Insight

Results achieved after months.

The Cloud-Native Solution: A Paradigm Shift

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Planetary Computer

A multi-petabyte catalog of environmental data with a flexible computing environment, bringing code directly to the data.

🧠

Aurora Foundation Model

A powerful AI model that forecasts weather and air quality at speeds thousands of times faster than traditional methods.

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Cloud-Optimized Tech

Using formats like COG & Zarr with STAC catalogs to enable efficient, on-demand data access without downloads.

The Integrated Learning Pathway

20-Week Timeline (7 hours/week)

Calculate your custom schedule based on the 140 total course hours.

1

Part 1: Foundational Azure Certifications

Weeks 1-6

Master the core cloud, AI, and data services that underpin the entire curriculum.

📜 AZ-900: Azure Fundamentals Study Guide (Weeks 1-2)

🧠 AI-900: Azure AI Fundamentals Study Guide (Weeks 3-4)

💾 DP-900: Azure Data Fundamentals Study Guide (Weeks 5-6)

Milestone: Achieve all three certifications.

2

Part 2: Geospatial Foundations

Weeks 7-10

Transition from theory to practice by learning the core tools and techniques of cloud-native remote sensing.

Key Resources:
3

Part 3: Advanced Models & Forecasting

Weeks 11-14

Dive deep into the architecture of large-scale AI and apply foundation models to real-world environmental challenges.

Key Resources:
  • Book: Understanding Deep Learning
  • Paper: "A foundation model for the Earth system"

Milestone (Week 14): Capstone Proposal Submitted.

4

Part 4: Capstone Project Execution

Weeks 15-20

Apply all learned skills to a research-grade project.

  • Weeks 15-16: Data Acquisition & Prep.
  • Weeks 17-18: Analysis & Modeling.
  • Week 19: Interpretation & Reporting. Milestone: Draft of Final Capstone Report Completed.
  • Week 20: Final Polish. Milestone: Final Capstone Project Submitted.

Course Structure & Impact

Time Allocation per Module

A breakdown of the 140-hour course, showing the distribution of time across the four major learning phases.

Accelerating Time-to-Science

Cloud-native workflows dramatically reduce the time from research question to scientific insight. Learn more about how NASA is increasing the speed to science.