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Certification

Data Science Certification Online

Statistics, SQL, experimentation and dashboards — the analytics half of AI, taught by people who have had to defend a number in a board meeting.

weeks
18weeks
case studies
4case studies
capstone
1capstone

What you get

How this one is different

Statistics that survive contact

Distributions, confidence intervals, hypothesis testing and the ways an A/B test quietly goes wrong.

SQL until it is boring

Window functions, CTEs and query performance, drilled against a realistic warehouse schema.

Dashboards people use

Power BI and Excel modelling, with a hard focus on the one number a stakeholder needs to see first.

Predictive modelling

Forecasting, churn and segmentation, framed as decisions rather than accuracy scores.

Detail

Syllabus

  • 01Python for data analysis
  • 02SQL and data modelling
  • 03Descriptive and inferential statistics
  • 04Experiment design and A/B testing
  • 05Visualisation, Excel and Power BI
  • 06Forecasting and predictive models

Questions

Before you start

This track spends more time on statistics, experimentation and communication; the ML course spends more time on algorithms. They share Modules 1 and 2.

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Begin the first module

Become AI native, it is the real deal today, and if it is not for you, you have lost nothing but learnt a new skill.

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