Overview
Machine Learning for Engineers is part of the AI, Digital Transformation & Cybersecurity track at Garnet Global Training Center. Practical AI, data and security skills for organisations moving their work onto digital platforms. The course is taught in English or Arabic as a 5-day or 10-day program, in classrooms in cities such as Dubai, Riyadh, Cairo, London and Istanbul, or live online, and it can be delivered in-house with examples and exercises built around your own operations.
What you will be able to do
- Explain the principles, terminology and standards that govern Machine Learning for Engineers.
- Apply proven methods and tools to real situations from your own workplace.
- Analyse performance gaps, risks and root causes, and choose the right response.
- Measure results with practical indicators and report them clearly to management.
- Leave with a personal action plan you can start using the following week.
Who should attend
Managers, IT and data professionals, analysts and digital transformation teams.
Key topics
- AI use cases and value mapping
- Data quality and governance
- Hands-on tools and prompting
- Security threats and controls
- Responsible AI and regulation
- Roadmaps and change adoption
5-day outline
Day 1 Foundations of Machine Learning for Engineers
- Scope, terminology and governing standards
- AI use cases and value mapping
Day 2 Methods and tools
- Data quality and governance
- Hands-on tools and prompting
Day 3 Application and case studies
- Security threats and controls
- Roadmaps and change adoption
Day 4 Performance, risk and compliance
- Responsible AI and regulation
- Measurement and reporting
Day 5 Workshop, assessment and action plan
- Hands-on workshop on a workplace challenge
- Final assessment and personal action plan
10-day outline
Day 1 Foundations of Machine Learning for Engineers
- Scope, terminology and governing standards
- AI use cases and value mapping
Day 2 Methods and tools
- Data quality and governance
- Hands-on tools and prompting
Day 3 Application and case studies
- Security threats and controls
- Roadmaps and change adoption
Day 4 Performance, risk and compliance
- Responsible AI and regulation
- Measurement and reporting
Day 5 Workshop, assessment and action plan
- Hands-on workshop on a workplace challenge
- Final assessment and personal action plan
Day 6 Advanced techniques and specialist practice
- Complex cases in depth
- Common mistakes and how to avoid them
Day 7 Digital tools, data and automation
- Analysis tools and software
- Using AI in this field
Day 8 Benchmarking against international practice
- Global performance benchmarks
- International case studies
Day 9 Capstone project
- Analyse a real challenge from your organisation
- Build the solution and implementation plan
Day 10 Presentations, final assessment and certificates
- Project presentations and review
- Final exam and certificate award
Certificate
Participants who attend at least 90% of sessions and complete the final assessment receive a certificate of completion stating 35 contact hours (5-day) or 70 contact hours (10-day).