Big Data Analytics on Fraud Detection

Objectives to cover:

PART A: DISSERTATION INFORMATION

A1. Introduction

A2. Aims and Learning Outcomes

A3. Styles

A4. Key Contacts and Dates

A5. Supervision

A6. Ethics

A7. Proposal

A8. Approval of Data Collection Instruments

A9. Academic Misconduct

A10. Format of Final Submission

A11. Confidentiality

A12. SubmissionA13. Marking.

PART B: SPECIFIC PROGRAMME INFORMATION

B1. Edinburgh Business School

APPENDICES

Appendix 1. General Marking Criteria (Dissertations)

Appendix 2. One Drive Data Submissions Guide

Reference:  Harvard style