Course Overview
Assess projects with sound economic and technical analysis.
Course Overview
Engineering and maintenance projects require rigorous evaluation to ensure technical feasibility, economic viability, and long-term value. This course is designed to equip professionals with the analytical frameworks and decision-making tools necessary to evaluate projects across their lifecycle. Combining financial modelling, technical assessment, and risk analysis, participants will learn how to justify capital and maintenance investments and optimise project performance in industrial and infrastructure settings.
What you’ll learn
By the end of this course, participants will be able to:
– Use industry-standard methods such as Net Present Value (NPV), Internal Rate of Return (IRR), and lifecycle cost analysis.
– Assess project alternatives based on risk, reliability, and engineering performance.
– Integrate cost-benefit analysis with maintenance planning and resource allocation.
– Make data-driven decisions to improve project efficiency and ROI.
Certification Details
Upon successful completion of this programme, participants will receive an Oxford Knowledge Certificate of Completion.
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Awarded by: Oxford Knowledge
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Format: Printed certificate with unique ID and optional digital verification
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Delivery: Issued at course completion or sent within 7 working days
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Recognition: Certificates validate participation in advanced, expert-led training aligned with global industry standards.
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Accreditation: Oxford Knowledge certifications represent advanced learning led by global experts. We are actively pursuing formal accreditations with top-tier institutions to further enhance your credentials.
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This certificate demonstrates your commitment to professional excellence and is a valuable addition to your leadership and development portfolio.
Requirements
- Ideal for engineers, project managers, maintenance planners, cost estimators, and technical supervisors.
- Familiarity with basic engineering or project finance concepts is recommended.
- English proficiency is required (course delivered in English).
- Participants should be prepared to work with numerical data and case-based analysis.
Instructor
