Early-Stage Startups
Designed for founders with an idea, prototype or early customers. It is especially useful for learners who need a structured, practical route into predictive analytics rather than a purely theoretical overview.
ESH-05710 · Data Science
Predictive Analytics Professional for Early-Stage Startups — Data Science
A 16-hour intermediate course for founders with an idea, prototype or early customers who want to develop workplace-ready and venture-ready capability in predictive analytics. The course combines the data science context with practical frameworks, realistic cases, guided exercises and a final applied output. Participants finish with a structured approach they can adapt to a real venture, team or project.
Blended online16 hoursIntermediateEarly-Stage StartupsBuild pathway
What you need
A current startup or validated venture concept is recommended.
European Startup Hub Certificate of Completion — Predictive Analytics Professional
Case analysis, structured assignments and a final implementation project.
Learning outcomes
What you will be able to do.
Outcome 1
Explain the core principles of predictive analytics in the context of data science.
Outcome 2
Diagnose a realistic predictive analytics challenge using structured startup tools.
Outcome 3
Build a practical predictive analytics output appropriate for early-stage startups.
Outcome 4
Evaluate evidence, assumptions and trade-offs before making predictive analytics decisions.
Outcome 5
Apply predictive analytics methods to a venture, project or organisational scenario.
Outcome 6
Create a next-step action plan that can be used after the course.
Full syllabus
10 course modules.
Each module combines explanation, examples and an applied activity.
Module 1
Foundations of Predictive Analytics
Practical study of foundations of predictive analytics with examples, prompts and an applied activity.
Module 2
The Data Science context
Practical study of the data science context with examples, prompts and an applied activity.
Module 3
Customers, users and stakeholder needs
Practical study of customers, users and stakeholder needs with examples, prompts and an applied activity.
Module 4
Tools and frameworks for Predictive Analytics
Practical study of tools and frameworks for predictive analytics with examples, prompts and an applied activity.
Module 5
Evidence, data and assumptions
Practical study of evidence, data and assumptions with examples, prompts and an applied activity.
Module 6
Designing the approach
Practical study of designing the approach with examples, prompts and an applied activity.
Module 7
Execution and operating decisions
Practical study of execution and operating decisions with examples, prompts and an applied activity.
Module 8
Measurement and key indicators
Practical study of measurement and key indicators with examples, prompts and an applied activity.
Module 9
Risks, ethics and common failure modes
Practical study of risks, ethics and common failure modes with examples, prompts and an applied activity.
Module 10
Case study: Predictive Analytics in practice
Practical study of case study: predictive analytics in practice with examples, prompts and an applied activity.
Assessment
Case analysis, structured assignments and a final implementation project.
Included materials
Digital course notes · Practical worksheets · Case exercises · Action-plan template · Completion record in ESH ID
Learning support
Platform learning support; live facilitator interaction is included where the delivery format states Live online or Blended online.
Course information & disclaimer
Educational programme. Completion does not constitute professional, legal, financial or investment advice and does not guarantee funding, employment or business outcomes. Catalogue version 2026.1 · Last reviewed 2026-08-24.
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Predictive Analytics Professional for Early-Stage Startups — Data Science · 16 hours · Blended online
Enrol for €340