First-Time Founders
Designed for people preparing to launch their first venture. It is especially useful for learners who need a structured, practical route into machine learning rather than a purely theoretical overview.
ESH-00912 · Artificial Intelligence
Machine Learning Practitioner for First-Time Founders — Artificial Intelligence
A 12-hour intermediate course for people preparing to launch their first venture who want to turn concepts into practical startup outputs in machine learning. The course combines the artificial intelligence 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 online12 hoursIntermediateFirst-Time FoundersBuild pathway
What you need
A business idea is useful but not required.
European Startup Hub Certificate of Completion — Machine Learning Practitioner
Applied exercises, one milestone submission and a final practical project.
Learning outcomes
What you will be able to do.
Outcome 1
Explain the core principles of machine learning in the context of artificial intelligence.
Outcome 2
Diagnose a realistic machine learning challenge using structured startup tools.
Outcome 3
Build a practical machine learning output appropriate for first-time founders.
Outcome 4
Evaluate evidence, assumptions and trade-offs before making machine learning decisions.
Outcome 5
Apply machine learning 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 Machine Learning
Practical study of foundations of machine learning with examples, prompts and an applied activity.
Module 2
The Artificial Intelligence context
Practical study of the artificial intelligence 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 Machine Learning
Practical study of tools and frameworks for machine learning 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: Machine Learning in practice
Practical study of case study: machine learning in practice with examples, prompts and an applied activity.
Assessment
Applied exercises, one milestone submission and a final practical 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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Machine Learning Practitioner for First-Time Founders — Artificial Intelligence · 12 hours · Blended online
Enrol for €230