Learning path
Data Professional
From SQL to decision-ready analysis, with pipelines that survive contact with real data.
- Level
- Beginner → Intermediate
- Estimated time
- 6-9 months
- Required builds
- 6 projects
- Guided study
- ≈ 220 hours
What you will be able to do
- 01Write SQL that answers ambiguous business questions precisely.
- 02Clean and model messy real-world data without hiding the mess.
- 03Build a pipeline that runs on a schedule and fails loudly.
- 04Present analysis that leads to a decision, not just a chart.
Curriculum
4 modules, in order
Stages build on one another. Nothing is optional, and nothing is repeated for length.
- M150h
Querying
Relational thinking, joins, window functions and query performance you can reason about.
- M270h
Analysis
Distributions, uncertainty, experiment reading and the statistics that get misused most.
- M360h
Pipelines
Ingestion, transformation, testing data, and scheduling work that survives bad inputs.
- M440h
Communication
Visual grammar, narrative structure and writing the caveats down.
Core skills
SQLPythonStatisticsPipelinesVisualisation
Prerequisites
- Spreadsheet literacy
- Basic statistics
- No prior Python required
How you are assessed
- Query challenges against a deliberately imperfect dataset
- Two end-to-end analyses with written methodology
- A stakeholder presentation reviewed for clarity
Roles this leads to
Data AnalystAnalytics EngineerData ScientistStart the Data Professional path
Talk to us about entry level, timing and how the reviews work.