Intro
Start here
Start with Data Foundations
Start with the language, formats, and habits that make data useful across teams.
Start with the language, formats, and habits that make data useful across teams.
4h
Start here
Course overview
Data
Turn raw data into trustworthy decisions by learning formats, pipelines, governance, and architecture without losing the meaning behind the numbers.
Start at the top, move stage by stage, then use practice and stage tests when you want a stronger check.
Stage 1 of 3
Data Foundations
Start with the language, formats, and habits that make data useful across teams.
Start with the language, formats, and habits that make data useful across teams.
M01
Module 1
What data is and why it matters
Data starts as recorded observations, for example numbers on a meter, text in a form, or pixels in a photo.
Use this sequence every time you inherit a metric or dataset.
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22 min
Open module
M02
Module 2
Data, information, knowledge, judgement
I want a simple model in your head that stays useful even when the tools change, and DIKW works because it forces you to separate raw observations from meaning before.
Suppose a dashboard shows “12.4”, which could be 12.4 kWh, 12.4 MWh, 12.4 percent, 12.4 incidents, or 12.4 minutes, so the number itself is not the problem and the missing context is.
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22 min
Open module
M03
Module 3
Units, notation, and the difference between percent and probability
Data work goes wrong when people are casual about units.
If one dataset records energy in kWh and another records energy in MWh, then the same physical quantity will appear with numbers that differ by a factor of 1000.
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22 min
Open module
M04
Module 4
Data representation and formats
Computers store everything using bits (binary digits) because hardware can reliably tell two states apart.
If any layer is unclear, teams will disagree while using the same data.
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22 min
Open module
M05
Module 5
Standards, schemas, and interoperability
Interoperability is a boring word for a very expensive problem.
A standard can be a file format (CSV, JSON), a schema (field definitions), a data model (how entities relate), or a message contract (API request and response).
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22 min
Open module
M06
Module 6
Open data, data sharing, and FAIR thinking
Open data is not “everything on the internet”.
Most real-world data lives in the middle: shared with specific parties under agreements.
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22 min
Open module
M07
Module 7
Visualisation basics (so charts do not lie to you)
Visualisation is part of data literacy.
Two charts show the same numbers.
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22 min
Open module
M08
Module 8
Data quality and meaning
Quality means data is accurate (close to the truth), complete (not missing key pieces), and timely (fresh enough to be useful).
Suppose we record response times for a service (in milliseconds): 110, 120, 115, 118, 5000.
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22 min
Open module
M09
Module 9
Data lifecycle and flow
Data starts at collection, gets stored, processed, shared, and eventually archived or deleted.
Each step has design choices: where to store, how to process, how to secure, and when to retire.
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22 min
Open module
M10
Module 10
Data roles and responsibilities
Roles exist so someone is accountable for quality, access, and change.
Data owners make decisions about purpose and access.
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22 min
Open module
M11
Module 11
Foundations of data ethics and trust
Ethics matters from the first data point.
Consent means people know and agree to how their data is used.
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22 min
Open module
Practice
Practice test
Data Foundations practice test
Test recall and judgement against the governed stage question bank before you move on.
Use this after the stage modules when you want to spot weak areas without the pressure of a timed assessment. Includes 20 published questions.
Self-paced
Open practice
Test
Stage test
Data Foundations stage test
Use the untimed stage test when you want a stronger stage-end check and no governed timed route exists yet.
Built from the published stage question bank so you can self-check honestly before the next stage. Includes 20 questions.
Self-paced
Open stage test
Stage 2 of 3
Data Intermediate
Move into models, pipelines, and applied analytics while keeping reliability in view.
How data systems are designed, governed, trusted, and analysed in real organisations.
Intro
Start here
Start with Data Intermediate
Move into models, pipelines, and applied analytics while keeping reliability in view.
How data systems are designed, governed, trusted, and analysed in real organisations.
3h
Start here
M01
Module 1
Data architectures and pipelines
Data architecture is how data is organised, moved, and protected across systems.
Imagine a daily batch pipeline that loads meter readings.
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20 min
Open module
M02
Module 2
Data governance and stewardship
Governance is agreeing how data is handled so people can work quickly without being reckless.
If a team shares a spreadsheet called “final_final_v7”, that is governance, just done badly.
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20 min
Open module
M03
Module 3
Interoperability and standards
Interoperability means systems understand each other.
A join works only if the key represents the same thing on both sides.
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20 min
Open module
M04
Module 4
Data analysis and insight generation
Analysis is asking good questions of data and checking that the answers hold up.
If two things move together, it might be causation, or it might be a shared driver, or it might be coincidence.
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20 min
Open module
M05
Module 5
Probability and distributions (uncertainty without the panic)
Data work is mostly uncertainty management.
If a pipeline succeeds 99% of the time, it still fails 1 day in 100.
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20 min
Open module
M06
Module 6
Inference, sampling, and experiments
Inference is the art of learning about a bigger reality from limited observations.
You analyse only customers who completed a journey because that is what is easy to track.
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20 min
Open module
M07
Module 7
Modelling basics (regression, classification, and evaluation)
Modelling is not magic.
If only 1% of cases are fraud, a model that always predicts “not fraud” gets 99% accuracy.
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20 min
Open module
M08
Module 8
Data as a product (making datasets usable, not just available)
A mature organisation treats important datasets like products.
If every request becomes a one-off extract, you are not serving data.
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20 min
Open module
M09
Module 9
Risk, ethics and strategic value
Data risk is broader than security.
Use this to build practical judgement, not abstract compliance language.
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20 min
Open module
Practice
Practice test
Data Intermediate practice test
Test recall and judgement against the governed stage question bank before you move on.
Use this after the stage modules when you want to spot weak areas without the pressure of a timed assessment. Includes 18 published questions.
Self-paced
Open practice
Test
Stage test
Data Intermediate stage test
Use the untimed stage test when you want a stronger stage-end check and no governed timed route exists yet.
Built from the published stage question bank so you can self-check honestly before the next stage. Includes 18 questions.
Self-paced
Open stage test
Stage 3 of 3
Data Advanced
Join up data architecture, streaming, governance, and product thinking for real systems.
Advanced data systems, mathematical foundations, and strategic decision making at scale.
Intro
Start here
Start with Data Advanced
Join up data architecture, streaming, governance, and product thinking for real systems.
Advanced data systems, mathematical foundations, and strategic decision making at scale.
4h
Start here
M01
Module 1
Mathematical foundations of data systems
Maths in data systems describes patterns, uncertainty, and change.
Definitions:
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40 min
Open module
M02
Module 2
Data models and abstraction at scale
Models are simplified representations of reality.
A team drops location data “because it is messy”.
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40 min
Open module
M03
Module 3
Advanced analytics and inference
Inference is about drawing conclusions while admitting uncertainty.
These are frequent sources of costly strategic mistakes.
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40 min
Open module
M04
Module 4
Data platforms and distributed systems
Data systems distribute to handle scale and resilience.
Eventual consistency can be perfectly acceptable for a monthly report.
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40 min
Open module
M05
Module 5
Governance, regulation and accountability
Regulation exists to protect people and markets.
Many organisations use a DAMA DMBOK style lens to describe data management capabilities.
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40 min
Open module
M06
Module 6
Data as a strategic and economic asset
Data creates value when it improves decisions, products, and relationships.
If every request becomes a one-off extract, you are not running a data capability.
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40 min
Open module
Practice
Practice test
Data Advanced practice test
Test recall and judgement against the governed stage question bank before you move on.
Use this after the stage modules when you want to spot weak areas without the pressure of a timed assessment. Includes 12 published questions.
Self-paced
Open practice
Test
Stage test
Data Advanced stage test
Use the untimed stage test when you want a stronger stage-end check and no governed timed route exists yet.
Built from the published stage question bank so you can self-check honestly before the next stage. Includes 12 questions.
Self-paced
Open stage test