Specialised Technical Course
Application of AI in Integration, Interpretation and Analysis of Big Geochemical Data
Develop a practical framework for integrating geochemical datasets and evaluating AI-assisted interpretations against geological evidence.
Course Overview
Examines AI-assisted integration and interpretation of large geochemical datasets. Participants consider data preparation, model assessment and the geological context needed to interpret results.
Who This Course Is For
- Geochemists working with analytical datasets
- Data analysts supporting subsurface interpretation
- Exploration geoscientists reviewing AI outputs
- Technical teams integrating geochemical data
What Participants Will Learn
Define an AI-assisted geochemical analysis question
Assess dataset compatibility and identify quality checks
Compare model choices against geochemical data coverage
Evaluate model results against validation and geology
Plan an analysis workflow with validation checks
Key topics
- Data integration
- Data quality
- Model assessment
- Geological interpretation
Course Modules
Back to Course OverviewGeochemical Analysis Objectives
Geochemical Analysis Objectives
Module overview
Define the interpretation question and the datasets needed for an AI-assisted analysis.
Key topics
Data integration · Data quality · Model assessment · Geological interpretation
Learning outcome
Participants can define an AI-assisted geochemical analysis question.
Learning format
Technical explanation · worked examples · guided exercise
Data Integration and Quality
Data Integration and Quality
Module overview
Review dataset compatibility, preparation and quality before model development.
Key topics
Dataset compatibility · Data preparation · Quality checks
Learning outcome
Participants can assess dataset compatibility and identify quality checks.
Learning format
Technical explanation · worked examples · guided exercise
Model Development Choices
Model Development Choices
Module overview
Compare model choices against the available data and the analysis objective.
Key topics
Model selection · Input features · Data coverage
Learning outcome
Participants can compare model choices against geochemical data coverage.
Learning format
Technical explanation · worked examples · guided exercise
Validation and Interpretation
Validation and Interpretation
Module overview
Assess model results using validation evidence and geological context.
Key topics
Validation evidence · Result consistency · Geological checks
Learning outcome
Participants can evaluate model results against validation and geology.
Learning format
Technical explanation · worked examples · guided exercise
Practical Analysis Review
Practical Analysis Review
Module overview
Outline an analysis workflow and explain checks needed before interpreting results.
Key topics
Workflow design · Validation plan · Interpretation limits
Learning outcome
Participants can plan an AI-assisted geochemical analysis with appropriate validation checks.
Learning format
Lectures, data exercises and interpretation workshop
Programme Information
Course duration, location, practical components, training-centre information and applicable certification arrangements depend on the selected programme.
Learning format: Lectures, data exercises and interpretation workshop
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