Introduction to Bachelor of Computer Science in Artificial Intelligence

Bachelor of Computer Science in Data Science program

Monash Graduate Attributes

Monash University prepares its graduates to be:

1. Responsible and effective global citizens who:

a. engage in an internationalised world

b. exhibit cross-cultural competence

c. demonstrate ethical values

2. Critical and creative scholars who:

a. produce innovative solutions to problems

b. apply research skills to a range of challenges

c. communicate perceptively and effectively

Program Education Objectives (PEOs)

The Bachelor of Computer Science in Data Science program expects to produce graduates, who are:

1.Competent in the field of data science.

2.Responsible and effective global citizens

3.Leaders in their chosen profession or society at large

Program Outcomes

The Bachelor of Computer Science in Data Science programme has developed a set of Program Outcomes (POs) for all of its graduates based on the competencies required by the Malaysia Qualification Agency (MQA)

Note:

1. These 11 POs are derived from the Seoul Accord
2. By comparing the 11 POs from the Seoul Accord with the Faculty Handbook’s 6 POs, the PO1 are the same across both the Seoul and Faculty Handbook.

PO1 Computing and Data Science Knowledge : Apply knowledge of computing fundamentals, mathematics, science, and  domain knowledge appropriate for the data science specialisation to solve complex computing problems

PO2 Problem Analysis : Identify and analyse complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing and data sciences, and relevant domain knowledge

PO3 Design/Development of solutions : Design solutions for complex computing  and data science problems and design systems, components or processes that meet specified needs

PO4 Research Investigation : Conduct investigations of complex computing and data science problems using research-based knowledge and methods including analysis and interpretation of data, and synthesis of information to provide valid conclusions

PO5 Modern tool usage : Create, select, or adapt and then  apply appropriate techniques, resources, and modern computing tools to complex computing and data science activities, with an understanding of the limitations

PO6 Computing Professionalism and Society : Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional practice and solutions to complex computing and data science problems

PO7 Ethics : Apply ethical principles and commit to professional ethics and responsibilities and norms of computing and data science practice

PO8 Communication : Communicate effectively with the computing and data science community about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions

PO9 Individual and team work : Function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary settings

PO10 Lifelong learning : Recognize the need for, and have the preparation and ability to engage in independent learning for continual development as a computing and data science professional.

PO11 Project management and finance : Demonstrate knowledge of project management, entrepreneurial principles and economic decision-making, and  apply these to manage projects