Daskerel Data and Statistics School / Data Scientist, Statistician, and Decision Analyst Learner
Progress from data literacy through inference, statistical learning, causal and Bayesian methods, production analytics, and postgraduate research.
Paid all-school membership
£34.80 including UK VAT (£29 before VAT) / month
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View prices and Stripe checkoutReleased digital scope
Public or synthetic datasets, statistical software, reproducible notebooks, databases, experiments, model evaluation, visualisation, and governance exercises.
Safety boundary
No uncontrolled personal or sensitive data, high-impact automated decisions, clinical or financial advice, re-identification, deceptive statistics, or production model deployment without review.
Academic alignment
This pathway progresses from UK Level 3 through Level 7 learning depth. It is Daskerel-authored education and does not itself award regulated qualifications, university credit, a bachelor's degree, or a master's degree.
Check official UK qualification comparisonsAcademic progression
Level 3
College foundation comparable in challenge to A level, T Level, or Level 3 diploma study.
Depth: Use spreadsheets, coding, descriptive statistics, visualisation, probability, and data ethics on safe datasets.
Entry: GCSE-level mathematics and English; no prior coding required.
Assessment: Clean dataset, analysis workbook, visual report, and data-ethics reflection.
Level 4
Introductory higher education comparable in challenge to a CertHE, HNC, or first undergraduate year.
Depth: Connect statistical inference, databases, reproducible programming, modelling, and guided data products.
Entry: Level 3 pathway evidence or equivalent quantitative knowledge.
Assessment: Reproducible data-analysis and statistical-modelling capstone.
Level 5
Intermediate higher education comparable in challenge to a DipHE, HND, foundation degree, or second undergraduate year.
Depth: Analyse multivariate, time-series, experimental, causal, machine-learning, and data-engineering problems.
Entry: Level 4 pathway evidence plus calculus, probability, and programming competence.
Assessment: End-to-end analytical product, experiment, model audit, and defended findings.
Level 6
Advanced undergraduate study comparable in challenge to a bachelor's degree final year.
Depth: Synthesize advanced statistical learning, Bayesian reasoning, causal inference, governance, and independent investigation.
Entry: Level 5 pathway evidence and competence in statistics, linear algebra, and software practice.
Assessment: Honours-style independent data research project, dissertation, reproducible repository, and presentation.
Level 7
Postgraduate study comparable in challenge to a master's degree.
Depth: Critically investigate complex data, advanced inference, scalable systems, decision science, and responsible research.
Entry: Level 6 pathway evidence or equivalent statistics or data-science degree-level capability.
Assessment: Research proposal, systematic evidence review, original reproducible analysis, master's-style dissertation, and viva.
Platform-wide module outputs
Concept, demo, checklist, lab, and assignment evidence.
Requirement, artifact, validation, risk note, and interview story.
Role-specific skill statement linked to a score or artifact.
Submitted evidence can support dashboard, readiness, and career exports.
Open materials
Certification objective coverage
This is the track-level audit view for blueprint alignment. Exact exam wording should still be checked against the current official provider guide before public exam-code claims are made.
data-science-statistics-pathway.data-literacy-collection-quality-and-ethical-use.01 / 5% weight
Implementation proof
Evidence requirements
data-science-statistics-pathway.descriptive-statistics-probability-and-distributions.02 / 5% weight
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data-science-statistics-pathway.spreadsheet-analysis-visualisation-and-communication.03 / 5% weight
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data-science-statistics-pathway.programming-foundations-for-data-analysis.04 / 5% weight
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data-science-statistics-pathway.statistical-inference-estimation-and-hypothesis-testing.05 / 5% weight
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data-science-statistics-pathway.databases-data-wrangling-and-reproducible-pipelines.06 / 5% weight
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data-science-statistics-pathway.regression-classification-and-model-evaluation-foundations.07 / 5% weight
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data-science-statistics-pathway.applied-data-science-and-statistics-capstone.08 / 5% weight
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data-science-statistics-pathway.multivariate-statistics-dimension-reduction-and-clustering.09 / 5% weight
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data-science-statistics-pathway.time-series-forecasting-experimentation-and-causal-foundations.10 / 5% weight
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data-science-statistics-pathway.machine-learning-feature-engineering-and-robust-evaluation.11 / 5% weight
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data-science-statistics-pathway.data-engineering-analytics-systems-and-production-workflows.12 / 5% weight
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data-science-statistics-pathway.advanced-statistical-learning-and-computational-statistics.13 / 5% weight
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data-science-statistics-pathway.bayesian-modelling-probabilistic-programming-and-uncertainty.14 / 5% weight
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data-science-statistics-pathway.causal-inference-responsible-data-science-and-model-governance.15 / 5% weight
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data-science-statistics-pathway.independent-data-science-and-statistics-honours-project.16 / 5% weight
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data-science-statistics-pathway.advanced-bayesian-causal-and-decision-modelling.17 / 5% weight
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data-science-statistics-pathway.large-scale-statistical-learning-data-systems-and-optimisation.18 / 5% weight
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data-science-statistics-pathway.data-science-research-governance-leadership-and-assurance.19 / 5% weight
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data-science-statistics-pathway.postgraduate-data-science-and-statistics-dissertation.20 / 5% weight
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Evidence requirements
Test readiness
Practice every domain in this track with exam-style questions, answer keys, and explanations.
Open mock testMost in-demand certification materials
CompTIA
Entry security, cloud security fundamentals, and broad IT baseline roles.
CompTIA Security+ is mapped to platform lessons and labs, but still needs a dated official-source review.
AWS
Beginners and career switchers who need cloud concepts, pricing, shared responsibility, global infrastructure, and core AWS service literacy.
CLF-C02 was verified against the official AWS certification page on 2026-06-24. Keep this source check on the 90-day review cadence.
AWS official-source stamp
Foundational / CLF-C02
Official domain weighting
Lab focus
Readiness gates
PeopleCert / ITIL
Support, operations, service desk, cloud operations, and team-lead learners who need service value, incident, change, SLA, and continual improvement fluency.
ITIL Foundation Version 5 is mapped to platform lessons and labs, but still needs a dated official-source review.
GitHub
Software, DevOps, cloud, data, and AI learners proving repository workflow, collaboration, issues, pull requests, and portfolio evidence.
GitHub Foundations is mapped to platform lessons and labs, but still needs a dated official-source review.
Google Skillshop
Design, marketing, product, and business learners who need GA4 events, conversions, audiences, acquisition, and reporting fluency.
Google Analytics Certification is mapped to platform lessons and labs, but still needs a dated official-source review.
Certification provider connections
CompTIA Certification
Use CompTIA objectives as the checklist, then connect Security+, Network+, or Cloud+ progress to the learner dashboard.
Booking partner: Pearson VUE
AWS Certification
Use the AWS Certification account to review exam guides, book exams, manage score reports, and share verified badges.
Booking partner: Pearson VUE or PSI, depending on exam and region
PeopleCert
Connect ITIL and service-management readiness to the learner's exam booking, certificate proof, and renewal reminders.
Booking partner: PeopleCert
GitHub Certifications
Connect repository, Actions, security, and collaboration evidence to certification readiness and portfolio exports.
Booking partner: GitHub exam delivery partner
Google Skillshop
Use Skillshop for Google product credentials and connect analytics or marketing evidence to learner progress.
Booking partner: Google Skillshop
01 Match
Map each Daskerel track to the official provider, exam code, registration page, and verification route.
02 Prepare
Use provider objectives with Daskerel lessons, mock exams, labs, and evidence packs before booking.
03 Book
Send learners to the official scheduling partner while keeping target dates and next actions in the dashboard.
04 Verify
Capture certificate URL, badge, expiry, renewal plan, and portfolio proof after the learner passes.
Study plan
Complete Level 3 foundations before attempting higher-education modules, unless prior evidence supports direct entry.
Progress through Levels 4 and 5 with reproducible practical work, critical analysis, and increasingly independent decisions.
Complete the Level 6 honours-style project before the Level 7 postgraduate research and dissertation stage.
Hands-on labs
Profile and clean a synthetic dataset with a data statement.
Build an honest visual analysis and explain uncertainty.
Run a statistical test and check assumptions and effect size.
Compare predictive models with leakage-safe validation.
Design a causal or Bayesian analysis and test sensitivity.
Complete an independent reproducible data study with governance, limitations, and human-review controls.
Track learning assets
Practice questions
The decision also requires validity, calibration, subgroup effects, uncertainty, privacy, fairness, explainability, monitoring, governance, and human accountability.
Versioned data provenance, code, environment, transformations, assumptions, random seeds, outputs, tests, and a clear interpretation boundary.