Data Science & Analytics
Turn raw data into decisions: learn to collect, clean, analyse and visualise data, build pipelines and predictive models, and communicate insights with free, step-by-step roadmaps.
About Data Science & Analytics
Data science is the practice of turning raw data into knowledge that people can act on. It combines statistics, programming and domain knowledge to answer questions such as what happened, why it happened, and what is likely to happen next.
The field covers several connected roles. Data analysts clean and visualise data to answer business questions, BI analysts turn it into dashboards, data engineers build the pipelines that deliver reliable data, and data scientists build predictive models, often using machine learning.
Most data work relies on a small set of tools: SQL for querying databases, a language such as R or Python for analysis, and charts and dashboards for sharing results. The roadmaps below take you from first analysis to modelling and data systems, whether you want a data career or simply want to make better decisions with numbers.
Where to start
A suggested order if you are new to data science. Each step builds on the one before.
Domains
Complete roadmaps for data roles, from first analysis to models and pipelines.
Data Analyst
Clean, analyse, and visualise data to answer business questions.
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BI Analyst
Turn business data into dashboards and actionable insights.
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Data Engineer
Build pipelines and infrastructure for large-scale data systems.
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Data Scientist
Extract insights and build predictive models from complex data.
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AI & Data Scientist
Apply statistics and machine learning to solve real-world problems.
View mapSkills
Focused tools you can learn on their own or alongside a domain.
