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Sector roadmap

Antimicrobial Resistance Surveillance

Genomic surveillance of antimicrobial resistance and outbreaks: bacterial WGS, AMR-gene detection, MLST/cgMLST typing, and integration with public-health dashboards.

ResFinderCARDMLSTGHRU
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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 AMRFinderPlus + ResFinder + Pathogenwatch 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 · documentation
WHO GLASS — global AMR surveillance
WHO
Why: Exact sector match (Antimicrobial Resistance Surveillance)
Dataset · tool
AMRFinderPlus
NCBI
Why: Exact sector match (Antimicrobial Resistance Surveillance)
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

AMRFinderPlus + ResFinder + PathogenwatchData wranglingQC & exploratory analysisVersion-controlled pipelines

Hands-on projects

Dataset deep-dive on ENA / NCBI pathogen + GHRU public isolates

Pick one study from ENA / NCBI pathogen + GHRU public isolates, 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 AMRFinderPlus + ResFinder + Pathogenwatch tutorial end-to-end on real data
  • Download and explore one full dataset from ENA / NCBI pathogen + GHRU public isolates
  • Document a clean QC + analysis pipeline that another person could rerun
Citation · course
Coursera · Antimicrobial Resistance
Coursera · Univ. of Dundee
Why: Exact sector match (Antimicrobial Resistance Surveillance)
Dataset · tool
ResFinder
DTU CGE
Why: Exact sector match (Antimicrobial Resistance Surveillance)
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

Outbreak genomic-surveillance brief

Take a public bacterial-isolate set, run an assembly + AMR + cgMLST pipeline, and write a one-page outbreak/typing brief.

Deliverable: Reproducible repo + cgMLST tree + 1-page surveillance brief

Milestones

  • Ship one original mini-analysis on a public dataset with clearly stated hypothesis and limitations
  • Engage with the Pathogenwatch and ESCMID-GS networks (post a question, answer one, or share a notebook)
  • Get peer feedback on at least one project and iterate
Citation · course
Python for Everybody
Coursera · Univ. of Michigan
Why: Exact sector match (Antimicrobial Resistance Surveillance)
Dataset · dataset
CARD — Comprehensive Antibiotic Resistance Database
McMaster
Why: Exact sector match (Antimicrobial Resistance Surveillance)
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 · book
R for Data Science (2e)
Hadley Wickham et al.
Why: Exact sector match (Antimicrobial Resistance Surveillance)
Dataset · tool
Pathogenwatch
CGPS
Why: Exact sector match (Antimicrobial Resistance Surveillance)

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 · Antimicrobial Resistance
Coursera · Univ. of Dundee
Python for Everybody
Coursera · Univ. of Michigan
LinkedIn Learning paths
LinkedIn

Trainings

Software Carpentry lessons
The Carpentries
Kaggle Learn
Kaggle

Documentations

WHO GLASS — global AMR surveillance
WHO
Git & GitHub fundamentals
GitHub Docs

Tools

AMRFinderPlus
NCBI
ResFinder
DTU CGE
Pathogenwatch
CGPS
EnteroBase — bacterial typing platform
Univ. of Warwick

Datasets

CARD — Comprehensive Antibiotic Resistance Database
McMaster

Books

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

Communitys

GHRU — Global Health Research Unit on AMR
GHRU

Typical career paths

AMR Bioinformatician

Runs bacterial WGS pipelines (assembly, AMR gene detection, MLST) for surveillance labs.

Public-Health Genomic Epidemiologist

Connects WGS outbreaks to epi data and supports response and reporting.

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