Module Details

Module Code: PHYS7039
Title: Prog for Instrum & Analysis
Long Title: Prog for Instrum & Analysis
NFQ Level: Intermediate
Valid From: Semester 2 - 2023/24 ( January 2024 )
Duration: 1 Semester
Credits: 5
Field of Study: 4411 - Physics
Module Delivered in: no programmes
Module Description: This module builds on the material covered in the Introduction to Programming for Measurement (PHYS6024) module to provide the student with the necessary skills to develop programs for measurement and instrumentation applications.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Apply visualisation and plotting techniques to data sets.
LO2 Design and implement programs for file system task automation.
LO3 Develop programs to access and manipulate data stored in a variety of file types.
LO4 Use generative AI to support the development of software applications.
LO5 Write software to acquire, parse and analyse data from scientific instruments.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
18073 PHYS6024 Intro Prog for Inst & Analysis
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Python Language
Modules. Scope of variables and code. Regular Expressions. Dictionaries. Run-time error avoidance and handling. Use of generative AI: prompt engineering, code generation and optimisation, code testing.
Data Acquisition and Instrument Control
Use of class libraries for data acquisition and instrument control, using common interfaces such as UART, VISA, SPI etc.
Data and File Handling
Reading from and writing to files in formats such as. .txt, csv, JSON. Character encoding: ascii, Unicode, utf-8, utf-16 etc., codecs module. File organisation: paths, directories etc. Use of Linux commands for basic file operations. Automation of file system tasks e.g. moving, copying, renaming. Os and shutil modules.
Data Analysis
Plotting and visualisation of data: matplotlib and seaborn. Data manipulation using pandas and numpy libraries: cleaning, transformation, sorting, calculation of descriptive statistics, simple linear regression.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Practical/Skills Evaluation % of Total Mark 20
Timing Every Second Week Learning Outcomes 1,2,3,4,5
Assessment Description
Lab programming exercises
Assessment Type Practical/Skills Evaluation % of Total Mark 40
Timing Week 6 Learning Outcomes 1,2,3,4
Assessment Description
Open Book Laboratory Exam
Assessment Type Practical/Skills Evaluation % of Total Mark 40
Timing Week 13 Learning Outcomes 1,3,5
Assessment Description
Open book Laboratory Exam
No End of Module Formal Examination
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of module content Every Week 2.00 2
Lab Contact Delivery and application of module content Every Week 2.00 2
Independent & Directed Learning (Non-contact) Non Contact Study and homework Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of module content Every Week 2.00 2
Lab Contact Delivery and application of module content Every Week 2.00 2
Independent & Directed Learning (Non-contact) Non Contact Study and homework Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
 
Module Resources
Recommended Book Resources
  • Al Sweigart. (2019), Automate the Boring Stuff with Python, 2nd. No Starch Press, [ISBN: 1593279922].
Supplementary Book Resources
  • Eric Matthes. (2023), Python Crash Course: A Hands-On, Project-Based Introduction to Programming, 3rd. No Starch Press, [ISBN: 1718502702].
  • M. Dawson. (2010), Python Programming for the Absolute Beginner, 3rd. Course Technology, [ISBN: 9781435455009].
This module does not have any article/paper resources
Other Resources