Module Code: H6DAPROJ
Long Title Data Analysis Project
Title Data Analysis Project
Module Level: LEVEL 6
EQF Level: 5
EHEA Level: Short Cycle
Credits: 10
Module Coordinator: Arghir Moldovan
Module Author: MICHAEL BRADFORD
Departments: School of Computing
Specifications of the qualifications and experience required of staff

Master’s degree in a computing or cognate discipline. May have industry experience also.
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Engage in practical data analysis activities in an effort to solve a challenging business or research problem
LO2 Explain and justify the selection and application of state of the art analytics tools and techniques in a data analysis scenario
LO3 Employ appropriate research methods to guide the analysis of data from the web
LO4 Convey the results of the work through judicious visualisation and written documentation.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
Co-requisite Modules
No Co-requisite modules listed
Entry requirements  
 

Module Content & Assessment

Indicative Content
Time and Project Management
This seminar will give students an overview of how to use their time effectively and how to manage multiple tasks at the same time. The primary focus will be on how a student can best manage their time to reach their project goals.
Version Control
This seminar will give an overview on how to use GitHub for code versioning. Students are requested to have a GitHub Account set up before attending this class.
Requirements Gathering
This seminar will give an overview on requirements gathering, a critical step in any project.
Academic Writing and Referencing
This seminar will give an overview on academic writing, how to reference correctly (including how to use a reference management system such as Zotero).
Conducting a literature review
This seminar will give an overview of how to conduct a literature review, including how to search for relevant research articles using online research engines and databases (e.g., Google Scholar, IEEE Xplore, etc.)
Presentation Skills
This seminar will contain an overview of how to present information clearly and effectively.
Understanding the Marking Scheme
This seminar will overview the marking scheme and how students to ensure that their project avails of the marking allowances.
Assessment Breakdown%
Coursework100.00%

Assessments

Full Time

Coursework
Assessment Type: Evaluation % of total: Non-Marked
Assessment Date: n/a Outcome addressed: 1,2,3,4
Non-Marked: Yes
Assessment Description:
Formative assessment will be provided both by the lecturer on an ongoing basis
Assessment Type: Project % of total: 100
Assessment Date: n/a Outcome addressed: 1,2,3,4
Non-Marked: No
Assessment Description:
Learners will implement a data analytics project
No End of Module Assessment
No Workplace Assessment
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
Reassessment Description
Learners who fail the Data Analytics Project module will be required to do a repeat project where all learning outcomes will be examined.

NCIRL reserves the right to alter the nature and timings of assessment

 

Module Workload

Module Target Workload Hours 0 Hours
Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Classroom & Demonstrations (hours) 24 Per Semester 2.00
Tutorial Other hours (Practical/Tutorial) 24 Per Semester 2.00
Independent Learning Independent learning (hours) 202 Per Semester 16.83
Total Weekly Contact Hours 4.00
 

Module Resources

Recommended Book Resources
  • Swetnam, D. Writing Your Dissertation: How to Plan, Prepare and Present Successful Work, How to Books..
Supplementary Book Resources
  • None.
This module does not have any article/paper resources
This module does not have any other resources
Discussion Note: