Course Overview
This course is targeted at engineers and energy professionals seeking practical and strategic insights into AI and machine learning for offshore wind and industry.
Course Highlights
The course is structured in two complementary parts:
Part A provides an introduction to the artificial intelligence and machine learning concepts that underpin industrial AI: knowledge representation, probabilistic reasoning, gradient based learning, neural network architectures, decision trees, time series analysis, and unsupervised learning techniques.
Part B builds on this technical awareness to address the strategic, regulatory, organisational, and commercial challenges of implementing AI in practice: strategy development, business case construction, compliance, cybersecurity, intellectual property, and change management. The learning ranges from building a working understanding of core machine learning concepts and their industrial relevance through to evaluating organisational readiness, building realistic ROI models, and navigating the regulatory landscape.
MAIN GOAL
The course addresses engineering and safety contexts, equipping learners with the critical thinking skills to make good technology choices.
Learning Outcomes
After completion of this course, you will gain the ability to:
- + Lead or contribute to AI strategy in offshore wind operators, energy companies, manufacturers, independent service providers, and technology consultancies serving these sectors.
Meet Your Instructors
Piotr Szczuko, D.Sc, PhD, Eng.
Course Coordinator
Assistant Professor
Admissions
Entry Requirements
- + Bachelor's degree in engineering, computer science, energy systems, data science, or a related technical discipline is recommended.
- + Recognition of prior learning is available for experienced industry professionals without formal qualifications.
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Application Deadline: TBC.
Practical Notes
- + Information on course materials to follow.
Fees & Funding
Tuition Fees
Visit institution page for information on fees and application deadlines.
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Course Info
Contact Piotr Szczuko, D.Sc, PhD, Eng. for any additional information relating to this course.