Demonstrate problem-solving skills in analysing a given problem(s)

Programming Support          0 credit

Academic Year                     2023-24

Table of contents 

Key team contact details 2

Module content 2

Learning materials 2

Maintaining Academic Honesty and Integrity 2

Meeting Deadlines 2

Getting Support 3

Preparing for your Assessment 3

Summative Assessments 3

Summative Assessment 1 3

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10 Appendix – Research ethics and integrity Error! Bookmark not defined.

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You are provided with study materials for your personal use only. You must not share these with others or upload them to websites. Any student who is found to have shared materials, particularly for personal gain, will be subject to disciplinary action if appropriate.

Module content

This module will provide students a critical understanding on the key programming principles and develop practical programming skills pertaining to mathematical and statistical foundations behind data science and artificial intelligence problems. This module covers a range of key concepts and methods from linear algebra, differential calculus, to probability theory and statistics, as well as the programming implementation of them.

Features of a programming language and how to perform particular operations will be demonstrated. You are advised to practise these activities yourself and, if appropriate, review results with peers. You will acquire hands-on experience of working on practical exercises and, if necessary, obtain help from a tutor. Programming is a highly practical subject, and you will learn a great deal from conducting programming exercises.

Learning materials 

The reading list for this module is available on Blackboard in the module area and online by searching readinglists. This shows real-time availability of books in the library and provides direct links to digital items, recommended by your lecturer.

Remember to log into Blackboard daily to receive all the latest news and support available at your module sites!

Subject guides (libraryguides) are also available to help you find relevant information for assignments, with contact details of the Subject Librarian for your School.

Maintaining Academic Honesty and Integrity 

Academic Integrity means avoiding plagiarism and cheating and owning your own work, the use of essay mills and AI content is also considered academic misconduct. This is when you submit a piece of work which is not completely your own, but which you are presenting as your own without acknowledging the author or properly referencing the original source. All your work must demonstrate Academic Integrity; it must be an honest and fair submission, complying with all the requirements of the assessment. Failure to meet these standards of behaviour and practice is academic misconduct, which can result in penalties being applied under the Academic Offences Regulations. You can get support with your academic writing by speaking to our Study support team.

Meeting Deadlines

You should always try your best to submit your work on time. You can submit coursework up to 10 calendar days late without penalty if you request an extension before the submission deadline. Without an extension, the maximum mark you will be able to get for that work will be the pass mark.

Getting Support

There may be times when you experience circumstances outside of your control and talking to your Module Leader and other support services available to you in the university will help keep you on track with your studies. You can access information on support services and further guidance at our Support for current students page.

If your circumstances mean that you are not able to submit at all or are unable to attend an in-person assessment like an exam or in-class test, then you can request mitigation for the assessment. Approved mitigation means that you can have another attempt without penalty if you fail an assessment or do not submit.

If you request an extension or mitigation before the deadline you can choose to self-certify, without providing evidence, so long as you have a valid reason.You can only self-certify three assessments per academic year.If you have used all your self-certification opportunities, or requested mitigation after the deadline, you will need to provide evidence of your exceptional circumstances for your request to be granted.

Your Students’ Union Advice Team will be able to support you through the process.

Preparing for your Assessment

A key part of your learning will be preparation for your summative assessment.You will be provided feedback on your formative assessments, and this will help you to better understand what is required of you when you submit your summative assessment. Please see below guidance on your formative assessment and how to access your feedback.

Summative Assessments

Summative Assessment 1

This is a 0-credit module.For MSc Bioinformatics students,you must complete all the programming exercises(located in the “Apply”section”of each weekly folder under “Learning Materials”) consolidate them into a single document, and submit it to Blackboard as an evidence of completion.This is required for submission in the Data Science for Bioinformatics module.Please note your submission will not be graded.

Assessment title

Portfolio* (MSc Bioinformatics only)

Submission date and time

Week 14

Word Count (or equivalent)

N.A

Where to submit

Blackboard

Feedback date

This work will not be marked

Assessment Weighting

N.A

PSRB requirements (if applicable)

N.A

Submitting, feedback & grades online using Blackboard

Main objectives of the Assessment

No.

Learning Outcome

Marking Criteria

 

1

Demonstrate problem-solving skills in analysing a given problem(s)

Technical understanding and knowledge

2

Develop software using different programming paradigms

Software programming practice and skills

3

Design and implement a solution to given problem(s) using programming

Technical solution design and evidence of implementation

 

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