Unit rationale, description and aim
The Python programming language is currently one of the world’s most popular programming languages. In the health sciences, Python is used by healthcare data analysts, clinical data analysts, epidemiologists, biostatisticians, data scientists and software engineers. This programming language has become an essential tool for addressing challenges in a variety of health fields, such as medical diagnostics, genomic sequencing, hospital management, biomarker detection, drug delivery and health informatics.
In this unit, students will learn to create increasingly complex algorithms that will develop their skills and knowledge of programming syntax, functions, data, and file management. In addition to this, students will also learn to utilise common library packages such as Numpy, Matplotlib and Pandas for describing, analysing, interpreting, and visualising data, and engage in machine learning activities that will require them to write code to solve problems in a variety of health-related contexts. This unit is an introduction to Python programming, and therefore while having prior experience with programming is beneficial, such familiarity is not required to engage with and succeed in this unit. This unit aims to help students understand and apply the fundamental concepts of the Python programming language.
Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
Demonstrate knowledge and understanding of fundame...
Learning Outcome 01
Apply common data processing library packages and ...
Learning Outcome 02
Solve problems in a variety of health-related cont...
Learning Outcome 03
Evaluate coding algorithms based on their quality,...
Learning Outcome 04
Content
Topics will include:
- Installing Python and Integrated Development Environments (IDEs)
- Library Packages: Numpy, Matplotlib and Pandas
- Variables and Data Types
- Data Structures
- Conditions and Loops
- Functions
- Classes and Objects
- Files and Exceptions
- Machine Learning
Assessment strategy and rationale
Educational literature shows that assessment drives learning. For this reason, assessments in this unit are designed to be engaging and interactive to encourage the active learner. The first assessment task is designed to ensure students have a solid understanding of the weekly content taught in the interactive workshops. Students will then engage with a variety of test questions that will assess their knowledge and understanding of fundamental programming concepts. The second assessment task will assess the student’s ability to use library packages to manage and present data. The final assessment task will require students to plan and develop their own machine learning code to solve problems in health-related contexts.
Overview of assessments
Assessment Task 1: Coding Tasks Students are requ...
Assessment Task 1: Coding Tasks
Students are required to demonstrate ability to read/write Python syntax and develop simple coding algorithms to solve problems in a variety of health-related contexts.
30%
Assessment Task 2: Data Analysis and Presentation...
Assessment Task 2: Data Analysis and Presentation
Students are required to demonstrate proficiency in using common Python library packages such as Numpy, Matplotlib and Pandas to analyse and present data to an industry-related standard.
30%
Assessment Task 3: Machine Learning Solutions Stu...
Assessment Task 3: Machine Learning Solutions
Students are required to apply their understanding of machine learning and develop sound code to address common issues in health data science.
40%
Learning and teaching strategy and rationale
Becoming a proficient programmer requires practice and application, and therefore this unit takes an active approach to learning. Interactive online workshop classes provide an opportunity for students to engage with and learn key programming concepts and to undertake activities that necessitate firm critical thinking and problem-solving skills. Online computer lab classes will permit students to practice coding programs through carefully paced modules and interactive exercises. Students will be supported in their learning via synchronous and asynchronous sessions, discussion forums and other resources made available to them through ACU’s Learning Management System (LMS).