Machine Learning · Fundamentals
机器学习 · 基础
Overview
Machine Learning · Fundamentals is part of our Digital & AI portfolio (Fundamentals). It runs as a 5-day or 10-day course, in the classroom in 40 cities or live online, and can be delivered in-house and customised for your organisation.
Available in English or Chinese, and as bilingual delivery for joint-venture and Chinese-led project teams in the Gulf and Africa.
You will be able to
- Explain the principles, terminology and standards behind Machine Learning.
- Apply Machine Learning methods to real cases from the Middle East, Europe and Africa.
- Build a solid base for further specialist study.
- Leave with templates and an action plan for your own workplace.
Who should attend
New staff, graduates and professionals moving into the field
Course outline
5-day programme (days 1–5)
Foundations and framework
- Course objectives, pre-assessment and scope of Machine Learning
- Key terminology and core concepts
- Automation and integration
- Cybersecurity and privacy
- Roles, responsibilities and interfaces
Principles and methods
- Use cases in industry and government
- Implementation roadmap and change
- Methods, procedures and documentation for Machine Learning
- Worked examples and guided practice
Tools, analysis and performance
- Concepts, architecture and terminology
- Data collection, quality and governance
- Calculations, checklists and decision tools
- KPIs and performance measurement
- Group exercise on a realistic scenario
Practical basics
- Step-by-step walkthrough of a typical task
- Tools and platforms in practice
- Do’s and don’ts for new practitioners
- Quiz and recap
Case study, assessment and action plan
- Case study: Machine Learning on a Middle East or African project
- Lessons learned and good practice
- Final assessment and feedback
- Personal and team action plan
The 10-day programme adds days 6–10
Advanced topics
- Advanced topics in Machine Learning
- Latest standards, editions and industry trends
- Analytics and visualisation
- Complex cases and non-routine problems
- Expert panel discussion
Digital tools and data
- Software and digital tools for Machine Learning
- Data analytics and dashboards
- Applying AI and automation
- Hands-on lab
Integration and management
- Integration with management systems and ISO standards
- Risk, cost and budget considerations
- Working with contractors and vendors
- Building the business case
Regional case studies
- Gulf case studies: UAE, Saudi Arabia and Qatar
- African case studies: Nigeria, Kenya, Egypt and Angola
- European benchmarks and regulations
- Peer review of participants’ own cases
Capstone project and certification
- Capstone project preparation
- Team presentations and expert feedback
- Final examination
- Certificate award and 90-day implementation plan
Where it runs
Middle East: Dubai, Abu Dhabi, Sharjah, Riyadh, Jeddah, Dammam, Al Khobar, Doha, Kuwait City, Manama, Muscat, Amman, Beirut, Cairo, Alexandria, Sharm El Sheikh, Baghdad, Erbil, Basra, Istanbul
Europe: London, Paris, Amsterdam, Barcelona, Madrid, Rome, Milan, Vienna, Geneva, Zurich, Munich, Berlin, Prague, Budapest, Lisbon, Brussels, Copenhagen, Stockholm, Athens, Edinburgh
Africa (in-house and live online): Lagos, Abuja, Port Harcourt, Nairobi, Johannesburg, Cape Town, Accra, Addis Ababa, Casablanca, Algiers, Tunis, Luanda, Dar es Salaam, Kampala, Kigali, Dakar, Abidjan, Kinshasa, Maputo, Tripoli
Live online for every time zone, including East Asia.