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In this course, the students will learn to architect, model, and implement data-driven business processes, data pipelines, and machine learning pipelines by applying Service-Oriented Architecture (SOA). SOA is a logical way of designing innovative, distributed software systems by providing value-adding services either to end-user applications or to other services distributed in the Internet, via published and discoverable interfaces. SOA enables building modular data pipelines, machine learning pipelines and business processes in the enterprises, and seamlessly integrating them to create value. The students are also taught to design an enterprise data platform architecture by applying data mesh, SOA, and domain-driven design.
The course includes both lectures and interactive labs. Lectures are to provide a solid conceptual foundation, and the labs are to provide the relevant practical experience.
At the end of the course, students will be able to:
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Understand and use the distributed data mesh as the enterprise data platform architecture
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Design service-oriented solutions for data-driven business processes, data pipelines, and machine learning pipelines in enterprises.
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Apply domain-driven design to identify data domains and services
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Explain, justify and apply the best practices, design principles and patterns in developing service-oriented solutions
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Document designed service-oriented solutions using open standards
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Implement designed service-oriented solutions using software technologies
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Evaluate designed service-oriented solutions in terms of operational requirements and quality criteria for enterprises
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Topics
Assessment and Grading Policy
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Assessment Type
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Details
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Total Marks from the Course Marks
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Group Project
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Design and Implementation of service-oriented applications that integrate data and processes in enterprise.
Assignment 1 (Implementation Part 1) - 10%
Assignment 2 (Design) - Design Report - 20%
Assignment 3 (Implementation Part 2) - 10%
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40%
(No Resit)
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Written Exam
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4 Open-ended Questions
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60%
(Have a Resit)
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The minimum requirement is 50% for each and 6 (out of 10) overall.
Course Materials
Due to the diversity of the topics of the course, there is no single book for the course. The sufficient study materials for each topic will be provided via Canvas.
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