Part A: Course Overview

Course Title: Python Programming Bootcamp

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

COSC3103

City Campus

Undergraduate

175H Computing Technologies

Face-to-Face

 Sem 1 2025

Course Coordinator: Rodney Ian Cocker and Kylie McColl

Course Coordinator Phone: +61 3 9925

Course Coordinator Email: rodneyian.cocker@rmit.edu.au and kylie.mccoll@rmit.edu.au

Course Coordinator Location: -

Course Coordinator Availability: contact via email


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


Course Description

Python Programming Bootcamp introduces programming in a bootcamp style. This course covers algorithmic development using standard control structures, fundamental concepts of programming and creation of small to medium software applications. It will further extend your skills in testing and debugging programs, and in the use of appropriate software technologies.

The course is delivered through a combination of self-learning material and face-to-face workshop sessions. The key concepts are introduced to you using interactive materials. Workshops are intended to facilitate and guide the learning process.

This course is tightly linked to COSC3106/3107/3108 Python Programming Studio, which should be taken right after (within the same semester). Python Programming Studio offers an extensive opportunity to apply concepts and skills learnt in this course over a realistic programming project.


Objectives/Learning Outcomes/Capability Development

Program Learning Outcomes

This course contributes to the program learning outcomes for the following program(s):

BP162P23 - Bachelor of Information Technology
BP349 - Bachelor of Information Technology (Professional)
BP355 - Bachelor of Cyber Security
BP356 - Bachelor of Cyber Security (Professional)
BP340P23 - Bachelor of Data Science
BP348 - Bachelor of Data Science (Professional)

PLO 1    Knowledge - Apply a broad and coherent set of knowledge and skills for developing data-driven solutions for contemporary societal challenges.
PLO 2    Problem Solving - Apply systematic problem solving and decision-making methodologies to identify, design and implement data-driven solutions to real world problems, demonstrating the ability to work independently to self-manage processes and projects
PLO 6    Responsibility and Accountability - Demonstrate integrity, ethical conduct, sustainable and culturally inclusive professional standards, including First Nations knowledges and input in designing and implementing data-driven solutions. 

For more information on the program learning outcomes for your program, please see the program guide.


Upon successful completion of this course, you will be able to:

  1. Explain and demonstrate a comprehensive knowledge of the fundamental concepts of programming.
  2. Design algorithmic solutions to a specific problem.
  3. Create programming solutions for small to medium-scale practical problems.
  4. Demonstrate good software development practices.
  5. Demonstrate skills for self-directed learning.


Overview of Learning Activities

This course will be facilitated in a bootcamp learning style, a focused mode of learning based on self-directed study and workshops, over nine weeks.

The content will be presented in a blended mode, with self-directed learning material (online) supplemented with workshop sessions. You will be actively engaged in a range of learning activities, such as instructor-guided activities, group-based activities and consultations.

Working in groups, you will identify, discuss and devise solutions to practical problems using, for example, theory, research, experimental data and your group’s collective creativity.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course. You will make extensive use of a provided online learning environment, which features curated interactive learning materials and a programming environment. You will be required to have your own personal laptop (BYOD) in order to access this environment in and outside of class. You will be able to access course information and learning materials through Canvas.

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

This course awards a pass or fail mark only. To be awarded a pass in this course, your total mark across all assessments must be at least 50/100.

Note: This course has no hurdle requirements.

Assessment Tasks

Assessment Task 1: Self-directed progress checking activities
Weighting: 20%
This task supports CLOs 1 and 5.

Assessment Task 2: Programming Challenge 1
Weighting: 15%
This task supports CLOs 2, 3 and 4.

Assessment Task 3: Programming Challenge 2
Weighting: 25%
This task supports CLOs 2, 3, and 4.

Assessment Task 4: Programming Challenge 3
Weighting: 40%
This task supports CLOs 2, 3 and 4.

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact your program manager or Equitable Learning Services if you would like to find out more.