CDI resources
Find a useful starting point for your data.
Explore guides and practicals to prepare data, analyse results, create charts, and explain your findings. Choose what fits your task—or ask us to help you find a starting point.
The guides below are free to read. Practical collections link to product pages with pricing and access details.
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Begin with a relevant task. You can use a guide for one step without working through the entire collection.
Data Science Foundations
Build foundations in Python, data preparation, analysis, and reproducible workflows.
Open guideVisualization with Python
Create and interpret clear charts with Python visualization tools.
Open guideDataset Discovery
Find public datasets and check their relevance, quality, and limitations.
Open guideExplore a specialist collection
Open a collection to see its guides.
Databases, machine learning & deployment · 3 guides
Databases & SQL
Organise, query, combine, and summarise structured data.
Open guideMachine Learning with Python
Explore model training, evaluation, interpretation, and reproducible workflows.
Open guideModel Deployment
Learn how to package, deploy, and maintain machine-learning applications.
Open guideOmics & bioinformatics · 6 guides
Data Acquisition System
Find and retrieve public sequencing data for reproducible analysis.
Open guideRNA-Seq Analysis
Explore count data, compare expression, and interpret biological findings.
Open guideGWAS Analysis
Explore association studies, data quality, analysis, and interpretation.
Open guideSingle-Cell Analysis
Explore quality checks, clustering, annotation, and interpretation.
Open guideMicrobiome Analysis
Prepare, compare, visualise, and interpret microbial community data.
Open guideProteomics Analysis
Prepare protein data, assess quality, analyse results, and interpret findings.
Open guideClinical & medical data · 1 guide
Clinical & Medical Data
Explore study design, data quality, statistical reasoning, and clear reporting.
Open guidePut your skills into practice
Explore focused tasks and outputs. Check each product’s description, requirements, and pricing before choosing.
Data Science Practicals
Practise data cleaning, exploration, visualization, and reproducible analysis.
Explore practicalsMachine Learning Practicals
Practise data preparation, model evaluation, interpretation, and deployment.
Explore practicalsCareer Development Practicals
Document skills and project evidence, and strengthen professional profiles.
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