- 作业标题： COMP1012 - Project I
- 课程名称：COMP1012 – Programming Fundamentals and Applications
- 完成周期：5天
Choosing your project
As part of your semester in COMP1012, you are expected to complete a fully-fledged Python
modeling project in a team-group of 2-3 students. Within a group, all the members should
participate in the project development and be responsible for some tasks (design, implementation,
testing, report writing, etc.). The steps 1 – 3 are mandatory for everyone to implement. However,
there is an opportunity to choose an application topic (1 – 8) from below that sounds interesting
to you and dig into it. The selection will be based on First-Come-First-Served-Approach. Once
chosen you cannot change it change it back.
Each application topic can be chosen by at most 13 student groups. To choose the application
topic you should register your team through this link and finalize the application topic by 31st
October 2023. Once you register your topic and team through the link you should also send me
an email (ammoham@polyu.edu.hk) citing your application topic choice to resolve conflicts if
more students register for a single topic. Failing to choose your group and application topic will
be considered that you chose to work on the project individually and an application topic will be
assigned to you randomly.
At the end of the deadline of this project (November 30, 2023), you’ll submit your work as
detailed as possible and you’ll present your findings in detail in LaTeX document. All the
LaTeX files, function files, datasets and all relevant material should be submitted.
No matter what you choose, the main goal is to design a solution that you think you can
answer using the techniques and libraries in Python and not just a question that you can look
up the answer for on the internet. If similarities are detected in the code, libraries used, reports or
any traces that prove the case of plagiarism will lead to 50% deduction of project points and each
member in the group will be graded on the remaining 50% of points through viva-voce.
Project Timeline
The following is a tentative plan for the timeline we’ll be following to ensure that you
successfully complete your assignment.
- Week 1 – Nov 2023: A 3-minute lightening pitching round presentation (< 3 min, 5
slides max; slide 1 for step 1, slide 2 for step 2 and step 3, slide 3 & 4 for application
topic and slide 5 for additional details) - Week 4 – Nov 2023: Semester project due. Late submissions will not be considered.
Project requirements
Project Pitching PPT = Weightage 5% – Every group should do a 3-Minute pitching during
Week 1 of November, 2023 to ensure you are not using the same concepts, libraries, etc. for
solving the project. A maximum of 5 slide PPT should be prepared (excluding the cover slide)
and should be uploaded on this link on or before November 01, 2023. Similarities in the projects
will not fetch your project full points and copying the ideas from the pitching round will still
make the copier lose points.
Project Report = Weightage 40% – A report should be writing in IEEE LaTeX document that
contains a 1) Cover page with title and the information of each team member 2) introduction 3)
related work 4) libraries/functions used and the design of the analytics program 5) Overview of
the dataset 6) algorithm with explanation 7) pseudo code with explanation 8) flowchart with
explanation 9) the analytics goal or hypothesis in each task and the corresponding analytics
results and meaningful simulation results that productively convey your algorithm/code, 10)
Summary of findings and conclusions conclusion, 11) source code with clear instructions on how
to execute your code on compiler 12) USP/Innovative work about your project 13) references
(optional) 14) Tasks performed by each member. There is no page limitation but avoid copy
pasting from the internet as plagiarism will lead to deduction of points.
Project execution = Weightage 55% – Your project code should execute successfully to any
applied datasets of images and article of words. Hence, it is strongly recommended that you find
a readily available dataset than creating yours.
Locating data and models
You’ll need to spend some time figuring out what model is the right model to use or what data
are available to answer your question. The internet is your friend for this part. You should be
able to find the details you need to compute your model or the data you want to analyze on the
web. These are some possible, non-exhaustive resources for locating data:
- Census and Statistic Department
- Data.gov - Hong Kong
- Kaggle
- Fivethirtyeight
- The Center for Disease Control
- Food and Agricultural Organization
- UNICEF
- World Health Organization
- World Bank
You may also wish to explore some of the additional resources listed on this page:
https://www.dataquest.io/blog/free-datasets-for-projects/
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