Innovative Problem-Solving Strategies for Advanced Data Science Projects
Explore a cutting-edge approach to tackling complex data science challenges, including problem statement formulation, motivation identification, related work analysis, unique approach development, evaluation planning, expected outcomes, and key references for further exploration.
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Presentation Transcript
[You can replace anything in [ ] with your statement. If you do not use it, delete [ ]. You can customize these presentation slides if you keep the CityU log and the same agenda.] [Capstone Title] [Your Name] [Submission Date] [Winter 2025] [Your Degree MSAI. MSCS, MSCY, or MSDS]
Agenda Problem Statement Motivation Related Work Approach Evaluation Plan Expected Conclusion Key References Q&A 2
Problem Statement [Describe what problem(s) you will solve to reduce the gap between what is known and what is not known. Use a question statement to describe your problem statement.] 3
Motivation [Show a motivation(s) for why you need to solve the problem? The motivation(s) comes from a key reference(s).] 4
Related Work [Who attempted to solve the same or similar problem? Key references are required for the related work.] 5
Approach [What approaches will you use to solve the problem? Explain how your approach is different from the related work.] 6
Expected Evaluation [Explain your plans of what data and how you will collect (data collection), how you will analyze them (data analysis), and what you can discover (findings).] 7
Expected Conclusions [Show what answers you will expect if you solve the problem.] 8
Key References [Show at least three key references. The key references show who attempts to solve the same or the similar problem.] 9
