MSc in Supply Chain Analytics
Analyze and optimize supply chain flows of goods, data, and resources with advanced analytics and decision-making tools.
Best for:Best for graduates or professionals with a background in computing, engineering, business, or mathematics seeking to specialize in data-driven supply chain optimization and analytics.
Overview
This master’s programme focuses on optimizing supply chain operations by leveraging data-driven decision-making. Students will study the movement, transformation, and storage of goods, people, data, and financial flows to enhance efficiency and performance across supply chains. The curriculum integrates business, technology, and analytics to prepare graduates for roles in logistics, operations, and supply chain management. Ideal for professionals seeking to specialize in high-demand analytical skills within supply chain ecosystems. The programme is delivered on campus with full-time attendance, offering a blend of theoretical knowledge and practical application.
What you'll do
- Develop analytical models to optimize supply chain flows and resource allocation.
- Apply advanced data analytics techniques to improve decision-making in logistics and operations.
- Analyze and interpret complex datasets to identify trends and opportunities for efficiency gains.
- Collaborate with industry partners to solve real-world supply chain challenges.
- Develop skills in process mining and performance evaluation for supply chain systems.
- Engage in case studies and projects focused on enhancing supply chain resilience and sustainability.
Requirements
Degree required: Honours degree with first or second-class honours, or equivalent qualification, in Computing, Science, Engineering, Business, Finance, Mathematics, or a related discipline.
Language: English (no specific proficiency test mentioned)
Instruction: English
- Strong analytical and problem-solving skills
- Proficiency in data analysis tools and techniques
- Basic understanding of supply chain operations and logistics principles
- Ability to work with large datasets and statistical software
- Familiarity with business and financial concepts
- Candidates without an Honours degree may be considered via Recognition of Prior Learning (RPL) if they have significant relevant experience.
- No specific nationality or residency restrictions mentioned.
Funding & terms
Programme and admissions
Admissions not verified
A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.
- Intake
- Not confirmed by the source
- Duration
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- Teaching language
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- Taught / research mode
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- Study mode
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- Campus
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- Prerequisites
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- Application instructions
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- Tuition
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- Funding
- Not confirmed by the source
How to apply
Deadline: Varies by intake (February for September start, October for January start; exact dates on course webpage)
Applicants should visit the ATU application portal to submit their application. The process involves filling out an online form, uploading required documents, and paying the application fee if applicable. Detailed instructions and deadlines are available on the programme’s webpage.
- CV or resume
- Academic transcripts
- Degree certificate
- Proof of English proficiency (if applicable)
- Statement of purpose or personal statement
- Letters of recommendation (if required)
Contact
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.