FLAGSHIP COURSE · SUMMER 2027 · ST ANDREWS, SCOTLAND
Practical Echosounder Data Processing
Five days of hands-on training using open-source tools to turn Simrad EK60/EK80 raw data into validated, quantitative outputs.
Work through real datasets, from initial inspection and quality control to feature detection, biomass estimation and reproducible workflows for reporting, modelling and machine learning.
TRAINING COURSES
Practical, specialist training in echosounder data processing, reproducible workflows, modelling and automation. The flagship course uses accessible open-source tools, including KORONA and echopype, while bespoke courses can be tailored to an organisation’s data, software and technical objectives.
Practical Echosounder Data Processing
A five-day, fully hands-on course taking participants from raw Simrad EK60/EK80 single-beam echosounder data through quality control, feature extraction, validation, biomass estimation and preparation of outputs for reporting, modelling and machine learning. Participants will use a range of open-source tools, including KORONA, echopype and supporting Python workflows. The emphasis is on understanding and applying complete processing workflows rather than mastering a single software package. No advanced programming experience is required. Guided examples, reusable templates and AI-assisted coding tools will be used to help participants build, adapt and understand practical workflows.
Planned course details
When: Summer 2027 – exact dates to be confirmed
Where: St Andrews, Scotland
Format: Five consecutive days, in person
Group size: Approximately 10–12 participants
Indicative fee: £600–£1,200 per participant, depending on participant category and final arrangements
Travel and accommodation: Not included
Register interest by: 31 January 2027
The course will cover
- Overview (physics/background/surveys/applications).
- Reading, organising and visualising Simrad EK60/EK80 raw data, using KORONA, echopype and other open-source processing tools.
- Understanding calibration information and core acoustic variables.
- Noise filtering, bottom detection and working with difficult datasets.
- Detecting features: fish schools, krill swarms and scattering layers.
- Feature classification, estimating abundance and biomass for stock assessment.
- Exporting structured outputs for reporting, statistical analysis and modelling.
Who the course is for
The course is aimed at scientists, analysts, consultants, postgraduate researchers and fisheries professionals who collect, process or interpret echosounder data. Some familiarity with acoustic data or scientific analysis will be useful, but advanced programming experience is not required.
Registration and payment
Registering interest is free and does not commit you to attend. Once the dates, venue and final course fee are confirmed, interested participants will be invited to book. Places will be secured following payment of an invoice.
Bespoke Training for Organisations
Training can be developed around an organisation’s own datasets, instruments, software environment and operational objectives. Courses can be delivered at client locations, in St Andrews, remotely or at another agreed venue. Content is tailored to participants’ experience, from introductory users to specialist technical teams.
Data collection and quality assurance
- Vessel-based echosounder and imaging-sonar workflows.
- Survey planning, system configuration and deployment.
- Data-quality assurance and early identification of acquisition problems.
- Practical procedures tailored to specific instruments and survey objectives.
Processing, analysis and automation
- Processing Simrad EK60/EK80 and related acoustic datasets.
- Open-source tools including KORONA, echopype and supporting Python workflows.
- Noise filtering, and bottom detection.
- Acoustic feature extraction and classification.
- Fish-school, krill-swarm and scattering-layer analysis.
- Biomass estimation, validation and uncertainty.
- Reproducible, automated and containerised processing pipelines.
- Statistical modelling, machine learning and operational decision support.
- Guided templates and AI-assisted workflows for participants with limited programming experience.
Format and cost
Course duration, content and technical level are agreed with the client. Training can range from focused one- or two-day workshops to longer practical courses combining instruction, demonstrations and supported hands-on analysis.
Following an initial discussion, Cupar Analytics will provide a proposed course outline, delivery plan and fixed quotation.
COURSE LEADER
Dr Roland Proud is a fisheries-acoustics and marine-data specialist with a PhD in Bioacoustics and Marine Ecology. He has more than 15 years’ experience working with echosounder datasets across academic research, commercial consultancy and applied fisheries projects.
His work combines acoustic data processing, quality control, feature detection, biomass estimation, statistical modelling, machine learning and the development of reproducible processing workflows. He has worked with vessel-based echosounder and imaging-sonar data across international fisheries research, ecosystem monitoring and operational applications.
Roland has organised and delivered international training in fisheries acoustics, R and Python, and has participated in more than ten marine and freshwater research surveys. His published work includes methods for detecting sound-scattering layers and automated classification of fish schools.
Course material will draw on real Simrad EK60/EK80 datasets, practical KORONA processing workflows and challenges encountered across research and commercial projects.
- PhD in Bioacoustics and Marine Ecology
- Founder and CEO of Cupar Analytics Ltd
- More than 15 years’ experience in fisheries acoustics and marine data analysis
- Experience delivering international workshops in fisheries acoustics, R and Python
Register interest for summer 2027
Complete the form below to receive priority notification when the dates, venue and booking arrangements are confirmed. Registering interest is free and does not commit you to attend.
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