| Course Title | Artificial Intelligence Group Project |
| Course Code | M-900-01 |
| Level | Master |
| ECTS Credits | 9.00 |
| Faculty/unit | Engineering Faculty |
| Field | Interdisciplinary course |
| Course Type | Standard |
| Course Leader | Pavlyuk Dmitry - Dr. sc. ing. professor |
| Annotation | This module will provide students with the opportunity to bring together knowledge and skills gathered throughout the study programme by conducting a project designing, implementing, evaluating and presenting an AI-based solution to a real-world problem.
Students work in small groups, selecting and using appropriate project management methodologies and tools. The work should involve making best use of the technical and human resources available to you.
A series of lectures by staff and guest speakers will present emerging problems of applied AI and state-of-the-art techniques for handling the issues that often arise during AI-based projects. |
| Aim | In this module, students will work in mixed-specialism groups to design, plan, and implement an AI-based project. |
| LO1 | Demonstrate logical examination of information and coherent rationale for decisions. |
| LO2 | Develop modern software solutions, integrating ethical, social, legal and economic aspects. |
| LO3 | Design, develop, maintain, test and evaluate a novel data analytic, machine learning, and/or artificial intelligence solution and apply this to a real-world context. |
| Required Literature | - Russell, S.J., Norvig, P., 2021. Artificial intelligence: a modern approach, Fourth edition. ed, Pearson series in artificial intelligence. Pearson, Hoboken.
- Agrawal, A., Gans, J., Goldfarb, A., 2018. Prediction machines: the simple economics of artificial intelligence. Harvard Business Review Press, Boston, Massachusetts.
- Dean, Jared, and Jared Dean. Big Data, Data Mining, and Machine Learning : Value Creation for Business Leaders and Practitioners, John Wiley & Sons, Incorporated, 2014. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/tsilv/detail.action?docID=1687540.
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| Assessment Method | Projects will be assessed according to the quality of both process and product. In addition to summative assessment, peer review will be used periodically to provide additional feedback and direction. Initial reflective report and proposal: This will be submitted at the end of phase 1 and will summarise the team’s learning and initial design and planning, with a proposal for the deliverable going into phase 2.Portfolio -this will consist of the teams’ process and design documentation during phase 2. Assessed presentation of project output and viva. At the end of the module, the team will present the results of the project to tutors / invited guests and will answer questions about the product and process. |
| Independent study | Independent study will cover reading of additional materials delivered in frame of the course and preparation of the reports and the solution. Also specific software tool will be explored in details during independent study. Team meeting also included in independent study. |
| Full-time |
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| First Sit Elements | Element Weighting, % | Group Work | Links to Results |
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| Reports | 100 | X | LO1, LO2, LO3 |
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