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Fisheries Science

Fisheries science integrates biology, ecology and quantitative modelling to assess fish stocks and inform sustainable harvest. Core tooling includes age-structured stock assessment models (Stock Synthesis SS3, ASAP, FLR), management-strategy evaluation, and regional bodies (ICES, NAFO, RFMOs).

FLRSS3ASAPICES
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Default learning track

4 phases · ~16–22 weeks

A baseline path through this sector with milestones, prerequisites, and concrete projects. Click Personalize this roadmap above to have the AI tailor pace, depth, and resources to your background and goals.

1

Phase 1 — Foundations

3–4 weeks 30–40 hours

Build the conceptual and quantitative base needed to read papers and follow tutorials in the sector.

Prerequisites

  • Comfortable with basic biology / health-science vocabulary
  • Ability to install software and use a terminal

Skills you'll build

Python or R basicsLinux shellGit/GitHubReading scientific literature

Hands-on projects

Reproducible analysis notebook

Walk through a published tutorial in Stock Synthesis (SS3) + R FLR and reproduce its results on the provided sample data.

Deliverable: GitHub repo with a Jupyter/Quarto notebook, environment.yml, and README

Milestones

  • Set up reproducible Conda/Mamba environment and a public GitHub repo
  • Read and summarize 3 review papers covering the sector landscape
  • Complete an intro statistics or scripting course end-to-end
Citation · course
Coursera · Sustainable Seafood (Univ. of Massachusetts)
Coursera
Why: Exact sector match (Fisheries Science)
Dataset · tool
Stock Synthesis (SS3)
NOAA Fisheries
Why: Exact sector match (Fisheries Science)
2

Phase 2 — Core tools & datasets

4–6 weeks 60–80 hours

Learn the standard analytical stack of the sector and the canonical public datasets used by professionals.

Prerequisites

  • Completed Phase 1 reproducible notebook
  • Working Python/R environment

Skills you'll build

Stock Synthesis (SS3) + R FLRData wranglingQC & exploratory analysisVersion-controlled pipelines

Hands-on projects

Dataset deep-dive on ICES stock assessments + RAM Legacy Stock Assessment Database

Pick one study from ICES stock assessments + RAM Legacy Stock Assessment Database, reproduce the headline result, and write a short technical note on what you found.

Deliverable: GitHub repo + 3-page PDF write-up

Milestones

  • Run the official Stock Synthesis (SS3) + R FLR tutorial end-to-end on real data
  • Download and explore one full dataset from ICES stock assessments + RAM Legacy Stock Assessment Database
  • Document a clean QC + analysis pipeline that another person could rerun
Citation · course
Python for Everybody
Coursera · Univ. of Michigan
Why: Exact sector match (Fisheries Science)
Dataset · tool
FLR — Fisheries Library in R
FLR Project
Why: Exact sector match (Fisheries Science)
3

Phase 3 — Applied projects

6–8 weeks 80–120 hours

Move from tutorials to original analyses on real questions. Start showing your work publicly.

Prerequisites

  • Phase 2 dataset deep-dive complete
  • Comfortable with the sector's primary tooling

Skills you'll build

End-to-end pipeline designStatistical interpretationScientific writingReproducible reports

Hands-on projects

Reproduce a small SS3 stock assessment

Reproduce a published small-stock SS3 assessment, perform a sensitivity run, and write an ICES-style advice brief.

Deliverable: Reproducible repo + diagnostics figures + 4-page assessment brief

Milestones

  • Ship one original mini-analysis on a public dataset with clearly stated hypothesis and limitations
  • Engage with the ICES and AFS quantitative-fisheries community (post a question, answer one, or share a notebook)
  • Get peer feedback on at least one project and iterate
Citation · book
R for Data Science (2e)
Hadley Wickham et al.
Why: Exact sector match (Fisheries Science)
Dataset · dataset
RAM Legacy Stock Assessment Database
RAM Legacy
Why: Exact sector match (Fisheries Science)
4

Phase 4 — Portfolio & career launch

3–5 weeks 30–50 hours

Package your work, target real roles, and prepare to interview in the sector.

Prerequisites

  • Phase 3 capstone project shipped
  • 2+ public repos under version control

Skills you'll build

Technical CVPortfolio siteInterview prep (case studies + technical questions)Networking

Hands-on projects

Job-ready portfolio package

Curate 2–3 of your strongest sector projects into a portfolio site with clear case-study writeups, plus a 1-page CV tailored to the target role.

Deliverable: Live portfolio URL + PDF CV + cover letter template

Milestones

  • Publish a portfolio site or pinned GitHub README linking to 2–3 projects
  • Tailor CV to 3 real job ads in the sector and submit applications
  • Practice 5 mock technical interviews with sector-specific case studies
Citation · training
Software Carpentry lessons
The Carpentries
Why: Exact sector match (Fisheries Science)
Dataset · dataset
FAO FishStat
FAO
Why: Exact sector match (Fisheries Science)

Curated learning resources

Verified, canonical resources from the official providers in this sector. The AI roadmap builder draws from this same library when it personalizes your roadmap.

Courses

Coursera · Sustainable Seafood (Univ. of Massachusetts)
Coursera
Python for Everybody
Coursera · Univ. of Michigan
LinkedIn Learning paths
LinkedIn

Trainings

Software Carpentry lessons
The Carpentries
Kaggle Learn
Kaggle

Documentations

Git & GitHub fundamentals
GitHub Docs

Tools

Stock Synthesis (SS3)
NOAA Fisheries
FLR — Fisheries Library in R
FLR Project
TAF — Transparent Assessment Framework (ICES)
ICES
openMSE — management strategy evaluation
openMSE
NOAA Fish & Fisheries Toolbox
NOAA Fisheries

Datasets

RAM Legacy Stock Assessment Database
RAM Legacy
FAO FishStat
FAO

Books

R for Data Science (2e)
Hadley Wickham et al.

Communitys

ICES — International Council for the Exploration of the Sea
ICES
American Fisheries Society
AFS

Typical career paths

Stock Assessment Scientist

Builds and runs stock-assessment models for national agencies or RFMOs (ICES, NOAA, etc.).

Fisheries Quantitative Analyst

Develops harvest-control rules, MSE and bio-economic models for fisheries management.

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