INT303编程辅导、讲解Data Analytics程序、c++，Java编程辅导讲解Python程序|讲解数据库SQL

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INT303 Big Data Analytics
Coursework and marking schema
Semester 1, 2020-2021
1. General Information
A. This coursework is the replacement of the closed/open book final
examination due to covit19.
B. It worth 70% of the total marks for this module and there is no resit and
retake.
C. This coursework will require approximately 1200 hours (number based
on group of 7 students – individual contribution around 150 -170 hours
(three to four full weeks).
D. You will be penalized for late or non-submission according to Xi’an
Jiaotong- Liverpool University regulations.
E. You are reminded of the need to comply with Xi’an Jiaotong-Liverpool
University’s guidelines to Academic Integrity.
F. Reports should be written in Word or PDF.
G. An electronic copy of each submission should be submitted to Learning
Mall, and a hard copy of each submission should be submitted to Dr.
Gangmin Li's submission box (located at the 4th floor of SD) using the
official Coursework Submission Cover Sheet.
2. Learning Outcomes Addressed
A. Demonstrate a solid understanding of processes and issues related to Big
Data Analytics;
B. Identify applications of BDA that can help improve business operations;
C. Determine the appropriate use of technologies, tools, and software
packages to support data analysis involving practical scenarios;
D. Be proficient with at least one data analytics software package.
3. Feedback
The formal feedback for this assignment will be available after the exam
board at the end of the semester. However, informal feedback can be
provided during the lab sessions or tutorial time if you are asking.
4. Instructions
This is a group assignment. Each group will consist of a maximum of 7
students within your lab practice group. As part of this exercise you must
look into the literature, textbook, and all the extra materials provided in the
source. You need identify a problem and a relevant dataset, choose a
suitable methodology and tools, analyze the data against the problem, and
make meaningful conclusions through a clearly identified and traceable
process.
You are expected to work in groups but you should write report
individually. You are expected to submit two reports and deliver one
presentation.
The three components will be individually marked based on 100
marks. Their percentage on the final mark is indicated in the braces.
You are also required to provide two individual 100 marks for your fellow
team mates.
1. Your personal section in the final project report to assess your fellow
team mate’s contribution in 100 marks
2. As a judge and listener to your fellow team mates' presentation and
mark their presentation in 100 marks
4.1 Report No. 1 -- Project Proposal (20% of 100 marks)
Prepare a three-page document detailing your plan. This does not need to be too
detailed, but needs to at least contain:
1. Individuals in the group.
2. Details about the problem:
A. What the problem is.
B. Why the problem is interesting – refer to the literature.
C. Relevant work – refer to the literature.
3. Information about the data source:
A. What data you plan to use.
B. Where you plan to get it from.
4. Proposed methodology (including subtasks, methods used in the analysis,
tools, processes etc.).
5. Final evaluation methods and criteria.
6. Potential limitations and challenges.
Please note that it is quite likely that the instructor will provide feedback and
alter or modify your proposed plans. This can either happen during the lab
sessions or will come in feedback on the specific proposal.
See below for a list of 50 useful data sources: https://learn.g2.com/open-datasources
Deadline: 11th of December 2020, 23:59 (Beijing Time)
4.2 Report No 2 -- Final Report (60% of 100 marks)
Your final report should be seven pages long. However, you will be allowed an
unlimited number of additional pages for references and appendices. This needs
to contain at least the following:
1. Explain the problem and motivation. You can borrow some material from your
proposal if you have not changed your plan.
2. Explain what data you explored, where it came from, and how you understand
it.
3. Explain what you did for preprocess with the data. You should present the ideas
in words instead of cut- paste your codes.
4. Explain what method you used to analysis the data.
5. How do you interpret you result.
6. Discuss limitations of your approach.
7. Discuss what you would do differently in the future.
A separate section in your final report addresses your personal
contribution and learning. The section must not be longer than 500 words and must
be attached to the Final Report. It must contain a discussion of the following
issues from your individual perspective.
a. A personal perspective of the problem addressed by the project. This may
include discussing the aims of the project, the benefits the project might offer
and to whom if it were successfully carried out, and the main benefits that
pursuing the project would offer the team members.
b. A critical appraisal of the methods applied to address the problem and manage
the project. This may include an evaluation of the methods used from your
perspective, a justification of why particular approaches have been taken and
why alternatives have not been used, a discussion of how effective the selected
approaches were and if, in hindsight, alternatives might have been better, a
discussion of how changes in the project plan and execution have been handled
and if the project execution progressed as initially expected, an evaluation of
how successful the project was and whether the results could be used to
continue the work, and suggestions for improving the approach to solving the
problem and the project management. Write this from your personal
perspective but relate this to the overall project.
c. Reflections on your contributions to the project. Discuss which parts of the
project you carried out/contributed to, how you approached these tasks and
how you interacted with other members, both in sharing your results and in
organizing the team’s activities. Also consider how your personal experience of
the project compared to your expectations and experience before you started
the project, how well your existing skills were utilized and what new skills you
have learnt. Justify why you should get the full percentage of the project mark.
d. Lessons learnt and advice for the future. Discuss what lessons you learnt from
executing the project about your discipline, project management and
teamwork. Consider how and where you might apply this in the future. The
content of your report must reflect the main items above. It is up to you how to
structure the report. You must write a reflective report about your group
project from your individual perspective. Whilst the above details are intended
to help you with deciding what to put in the report, they are not necessarily
complete nor should be used as section headings.
e. Peer review. Briefly discuss the contributions of each member and give a
grade for each of your team members (100 marks maximum).
Note, the report must not copy material from any of the team reports
but may refer to the content of the team reports.
Deadline: 27th of December 2020, 23:59(Beijing Time)
4.3 Presentation (10% of 100 marks)
You are required to make some slides (no more than 15 pages) and give a talk (5
minute) in front of your lab group (or using Zhumu). I hope to see the following
elements in your talk.
1. What is the problem and data you worked on?
2. What were the key ideas in your approach?
3. What techniques did you use?
4. What conclusions you came up with?
5. How do you evaluate and interpret your result?
6. What did you learn from the project?
Presentations will take place during the scheduled Lecture and Lab
session on the week 16 and 17 (28th December to 8th Jan 2021).
You will also be acting as a judge to mark your fellow team mates’
performance with 100 marks.
5. Marking Criteria for the Assessment
Credit will be awarded based on marker’s academic judgment based the following
criteria.
5.1 Reports:
A. Report No 1 – Project Plan:
1. How well you understand the problem and the base data?
2. How well you understand the analytical problem is a detective work?
3. How well you understand data analyzing is to find insight of data?
4. How well you understand the solution is never 100% satisfactory?
B. Report No 2 - Final report:
1. How well you can demonstrate you understand the data process
procedure?
2. How well you can assess data quality and quantity?
3. How well you can manage data preparation methods?
4. How well you can chose from many data analysis methods and use one
you choose well?
5. How well you can make data analyzing report?
6. How well you can interpret your results?
7. Did you consider legal, social, ethical and professional issues to justify
your choices and evaluate their results?
8. How well justified conclusions and concise discussion of future work?
5.2 Presentation:
1. Coherent and detailed presentation of the solution to the problem, focusing
on major challenges of the particular tasks in the project.
2. Evidence of testing and evaluation with clear statements of what the solution
is provided and what conclusion is reached.
3. How well you did in the project in comparison with other students?
4. How well you can work with teammates and you can appreciate others
contribution?
6. Overall Mark Calculation
Your final mark will be calculated based on the following formula:
Final mark = Mark_Report1 × 0.2 + Mark_Repor2 × 0.6 + M_pre × 0.1
+ Average (student mark_project) + Average (student mark _pre)/2 ×
0.1

INT303编程辅导、讲解Data Analytics程序、c++，Java编程辅导 讲解Python程序|讲解数据库SQL

INT303编程辅导、讲解Data Analytics程序、c++，Java编程辅导讲解Python程序|讲解数据库SQL