代做Business Analytics帮做Python程序

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Assignment Remit

Programme Title

MSc Accounting

Module Title

Business Analytics

Assignment Title

Individual analytics portfolio

Level

M

   Weighting

20%

Assignment Length

6 analytics tasks with commentary

Submission Format

Online

Individual

Assignment:

This assignment is based on the analytics tasks in Tableau completed in seminars during the module as well as the requirement for you to complete the Python module from datacamp below.

https://app.datacamp.com/learn/courses/intro-to-python-for-data-science

The aim is for you to build up a personal portfolio of completed tasks that show you developing skills. We want you to build the confidence to develop your own solutions to data manipulation and communication tasks as well as your technical skills in Excel, Python and Tableau. Developing these skills will allow you to contribute to the group assessment task in full.

The five Tableau seminars will start with basic Tableau analytics tasks and will build up to complex dashboards and data stories. This will be a learning journey for you and this assignment will help you record and reflect on your progress. Each task will be handed out before the seminar, and you will have a chance during the seminar and afterwards to develop and refine your own work. For each task we will be using the Tableau software that  forms the core of the module’s technical content and you should provide a link to your work by uploading it to the tableau public gallery.

In your portfolio we will require you to provide a short reflection on what you learned undertaking the task, the strengths and weaknesses of your solution and how the skills developed may be used in other tasks. This will also include reflections on the programming language Python as well as work with Excel.

You will be required to reflect on your use of Tableau verbally in a seminar and this will form part of the assessment criteria.

Module Learning Outcomes:

In this assessment the following learning outcomes will be covered :

•   Select, apply, and evaluate common analytics techniques and implement them using appropriate software tools.

•    Develop solutions to analytics problems using Python.

Grading Criteria:

Please see marking rubric below

Feedback to Students:

Both Summative and Formative feedback is given to encourage students to reflect on their learning that feed forward into following assessment tasks. The preparation for all assessment tasks will be supported by formative feedback within the tutorials/seminars. Written feedback is provided as appropriate.  Please be aware to use the browser and not the Canvas App as you may not be able to view all comments.

Plagiarism:

It is your responsibility to ensure that you understand correct referencing practices. You are expected to use appropriate references and keep carefully detailed notes of all your information sources, including any material downloaded from the Internet. It is your responsibility to ensure that you are not vulnerable to any alleged breaches of the essment regulations.


Criteria

Ratings

Pts

Tableau and Excel Tasks completed?

Has a full set of

completed Tableau tasks been uploaded to the Tableau

Gallery?

Have Excel seminar questions been

included in the portfolio.

(50%)

50 pts

40 to >28 Pts Distinction

Complete set of tasks uploaded with answers completed to a

good standard. This will include evidence of Excel and Tableau and may include some Python

coding.

28 to >24 Pts Merit

Complete set of answers

uploaded from both Excel and Tableau.

24 to >20 Pts Pass

Tableau and Excel Answers have been uploaded but

maximum of 1 are

incomplete or missing.

20 to >0 Pts Fail

Answers not

uploaded and/or are all

incomplete



Criteria

Ratings

Pts

Python Certification from Datacamp

Has the Introduction to python course on datacamp been

completed with

appropriate personal certification?

(5%)

5 pts

comp(ficate)lishmen(include)t(d) with clear evidence of student’s award

Tableau Skills

Has the student

displayed skills in Tableau use other than replicating

answers worked on in seminars?

(25%)

25 to >17.5 Pts Distinction

Detailed commentary on each activity included alongside

additional information. Work is innovative and competed to a very high standard

17.5 to >15 Pts Merit

All answers show original work

beyond

techniques used in class.

15 to >12.5 Pts Pass

Answers just about cover what was

expected in classes.

12.5 to >0 Pts Fail

Answers do not cover

work done in class.

25 pts


Criteria

Ratings

Pts

Reflective

Commentary

Has a reflective

commentary on each task been

completed? (0%)

20 pts

20 to >14 Pts Distinction

Detailed commentary on each answer

uploaded to a high standard.

14 to >10 Pts Merit

Commentary on each

answer uploaded that

evidence some thoughtful reflection.

10 to >8 Pts Pass

Commentaries

completed but not to a high standard.

8 to >0 Pts Fail

Answers not

uploaded and/or are all incomplete

Total points: 100



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