| 1. | Online quiz (12 minutes) | 5% | - 2 - Choose appropriate supervised or non-supervised learning techniques for complex real-world applications through critical analysis and application of established machine learning theories.
- 5 - Critically analyse and identify possible ethical impacts of using Machine Learning (ML) and Artificial Intelligence (AI) tools.
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| 2. | Machine learning coding exercise (800 - 1000 words report explaining the implementation and validating code using appropriate test cases. The length of code will be around 800 - 1000 lines) | 25% | - 1 - Critically evaluate and apply established machine learning and AI workflow and tools to synthesize complex information and develop predictive models.
- 2 - Choose appropriate supervised or non-supervised learning techniques for complex real-world applications through critical analysis and application of established machine learning theories.
- 3 - Apply and validate machine learning tools for developing innovative solutions and synthesizing complex information for solving real-world problems.
- 4 - Implement, validate and critically analyse machine learning algorithms.
- 6 - Interpret and communicate technical information effectively to technical and non-technical users especially at management level.
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| 3. | Artificial Intelligence Group Project 1 (6-8 minute presentation each) | 30% | - 1 - Critically evaluate and apply established machine learning and AI workflow and tools to synthesize complex information and develop predictive models.
- 2 - Choose appropriate supervised or non-supervised learning techniques for complex real-world applications through critical analysis and application of established machine learning theories.
- 3 - Apply and validate machine learning tools for developing innovative solutions and synthesizing complex information for solving real-world problems.
- 4 - Implement, validate and critically analyse machine learning algorithms.
- 5 - Critically analyse and identify possible ethical impacts of using Machine Learning (ML) and Artificial Intelligence (AI) tools.
- 6 - Interpret and communicate technical information effectively to technical and non-technical users especially at management level.
- 7 - Communicate technical information, related to ML and AI, effectively to non-technical users especially at management level
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| 4. | Artificial Intelligence Group Project 2 (1000 - 1250 words each) | 40% | - 1 - Critically evaluate and apply established machine learning and AI workflow and tools to synthesize complex information and develop predictive models.
- 2 - Choose appropriate supervised or non-supervised learning techniques for complex real-world applications through critical analysis and application of established machine learning theories.
- 3 - Apply and validate machine learning tools for developing innovative solutions and synthesizing complex information for solving real-world problems.
- 4 - Implement, validate and critically analyse machine learning algorithms.
- 5 - Critically analyse and identify possible ethical impacts of using Machine Learning (ML) and Artificial Intelligence (AI) tools.
- 6 - Interpret and communicate technical information effectively to technical and non-technical users especially at management level.
- 7 - Communicate technical information, related to ML and AI, effectively to non-technical users especially at management level
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