| CODE | CIS5002 | |||||||||
| TITLE | Computing for Scientists | |||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | |||||||||
| MQF LEVEL | 7 | |||||||||
| ECTS CREDITS | 5 | |||||||||
| DEPARTMENT | Computer Information Systems | |||||||||
| DESCRIPTION | This study-unit is a lecture-based study-unit with practicals held in class during the lectures. The topics covered include: - Use of UNIX-based operating systems, such as Linux; - Overview of Python, a programming language that can be used in various scientific contexts; - Overview of important data structures and libraries in Python (pandas, numpy, etc). Study-unit Aims: The aims of the study-unit are to: i) Introduce the best practices, standards, techniques, and concepts when using different operating systems and tools; ii) Provide students with an understanding of the Linux command line and how to write simple Bash scripts; iii) Assist students in using command-line bioinformatics tools to build pipelines to process Biological data; iv) Evaluate which libraries are most useful for performing a particular task; v) Assist studens in writing Python scripts for Bioinformatics related tasks. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: 1) Have an in-depth knowledge of how to use Linux, including installing software from repositories and from source; 2) Create Bash scripts to automate the process of creating a repeatable pipeline; 3) Use the Linux Terminal to run Bioinformatics tools in sequence; 4) Construct common Bioinformatics tasks in Python; 5) Use common Bioinformatics libraries in Python. 2. Skills By the end of the study-unit the student will be able to: 1) Use Bash and Python to solve common programming skills in Bioinformatics; 2) Search for state of the art libraries to solve domain specific problems; 3) Develop analytical skills to better understand the problem; 4) Use appropriate modelling techniques to model the data to remove redundancy; 5) Design a pipeline using Bioinformatics applications in Linux. Main Text/s and any supplementary readings: Course notes available on VLE. - Dawson, M. (2010). Python programming for the absolute beginner. 3rd ed. Boston, MA: Cengage Learning. - McKinney, W. (2014). Python for data analysis (1st ed.). Sebastopol: O'Reilly. - Cannon, J. (2014). Linux for beginners (1st ed.). CreateSpace Independent Publishing Platform: Amazon. - Oppel, A. (2009). Databases (1st ed.). New York: McGraw-Hill. |
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| STUDY-UNIT TYPE | Lecture, Independent Study & Tutorial | |||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | John M. Abela Joseph Bonello (Co-ord.) Jean Paul Ebejer Gianluca Valentino |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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