代做ACCFIN5246 Data Science and Machine Learning in Finance 2023/24代做回归

Assessment Brief 2023/24

Course Code	ACCFIN5246
Course Title	Data Science and Machine Learning in Finance

1. Question

The problem sheet will be distributed during the semester. The contents will include the learning outcomes associated with the workshops and reading material in the course.

2. Assessment Rubric/Criteria

The assessment is graded based on the methodological implementations, the precision of results, and the relevance of the comments provided to interpret results. The numerical precision bears a primary weight (2/3) followed by comments to interpret the financial implications (1/3).

3. Feedback

Feedback is provided following the deadline and submission of the report by all class participants.

4. Submitting

Submit your coursework using the named submission linkin the Assessment Section of your Course Moodle page. Take care to submit by the deadline or you may face lateness penalties.

Document creation - Individually Written

•    Please name files in the following way:  StudentID_CourseCode_QuestionNo.  e.g.

7299019_ACCFIN5246_1.  If there is no question choice, use 1 as the default.

•    The file type must be saved as .doc, .docx, .xls, .xlsx or .pdf.

•    Include your student ID in your document, ideally in the header on each page with the course code and title,e.g. 2489545_ACCFIN1003_Finance1.

• The maximum file size limit on Moodle is 230MB

5. Student conduct

Referencing and bibliography

For information, please goto the University Library webpage.

Plagiarism

For advice and more information, please goto:

• Student Learning Development web pages

• University Plagiarism Statement

If you make use of AI at any point in your research or writing process, no matter at what stage, you must acknowledge the use of that source/platform. as you would any other piece of evidence/material in your submission.

Turnitin

Your coursework will be processed through Turnitin for similarity checking.  You can submit a draft of your coursework to Turnitin before submitting your final copy.  You will find information about   using Turnitin in the Student Information Point Moodle [PSIP]

6. Generative AI

Generative AI offers many new opportunities for learning and the development of academicskill although, like any technology, it must be used judiciously. Students should consider the data protection and privacy issues that can becaused by using AI.  Consider how your personal information will be used before signing up to AI tools and ensure you read any data protection policies before interacting with AI. You should not feel pressured into using AI tools if you are uncomfortable with the data protection or privacy issues.  Bear in mind that responses to AI queries can be biased due to the inherent biases present in their training data.  This can lead to unfair and discriminatory responses. We strongly recommend that you treat AI with caution: AI tools do not know the meaning of what they produce, cannot be critical and evaluative, and are prone to biases, inaccuracies and mistakes.  Further information can be found here.