Introduction to Artificial Intelligence and Data Science

Module Description

The Module has two parts. The first part of the Module will equip learners with the basic understanding of what AI is, its importance and impact on the industry, business and society, and AI applications in various sectors including finance, healthcare, education, and government.

Learners will also learn various components of AI, including knowledge representation, reasoning, decision making and problem-solving. Learners will also get an exposure of some of the AI tools such as Rapid miner, Weka and R.

The second part of the Module will equip learners with the data science background required for AI and its applications.

It will include data exploration, preparation, representation, transformation, modelling, visualisation and presentation.

Entry Requirements

Candidates who apply for this course will possess:

• A related qualification at MQF Level 4

and/or

• Two ‘A’ Levels (MQF Level 4) or equivalent one of which should be related to Accounts, Business or Economics and a pass in English Language and Mathematics at MQF Level 3 (‘O’ Level or equivalent).

• Preference will be given to applicants having 1 year work experience related to the study programme.

In the case of students who do not possess all the formal required academic qualifications, then the Recognition of Prior Learning (RPL) process could be applied such that if evidence of equivalent learning is found then the applicant could still be accepted in the course.

Such RPL process will subject applicants to an interview held with a board of experts within the field, chosen specifically by IDEA Academy, so as to verify their experiences and prior learning.

Students whose first language is not English and do not possess an ‘O’ level pass in English Language will be required to demonstrate English language capability at IELTS level 6.0 or equivalent. 

Target Audience

• Individuals seeking to advance their academic and professional knowledge in Accounting.
• Individuals wanting to pursue a wide range of accounting, consulting, financial and managerial career paths.
• Individuals wanting to enhance their ability to interpret, assess and communicate financial related data.

Module / Unit Instructions

The proposed structure comprises a blended approach promoting the building of a community of practice via peer-to-peer learning. The structure uses primarily two dimensions of teaching-learning modes:

• Face to Face sessions

Face-to-face sessions include lectures, tutorials, discussions, presentations and workshop activities promoting peer-to-peer learning.

• Online Learning Activities

Online learning activities incorporate tutorials and asynchronous discussions. These may consist of active interaction, participation and contributions in fora discussions, sharing resources and self-reflection exercises. Learners also contribute to the building of the community of practice by providing feedback to their peers as critical friends, enhancing the learner’s critical engagement throughout the study period.

How you’ll be assessed

The course comprises:

• Evening classes for part-time courses.
• Classes held throughout the day for full-time courses.
• Guided learning, presentations, comprising synchronous online discussions, tutorials and/or videos.
• Self-study hours comprising research, reading and assignment work.

Assessment

Assessment is carried out via two mandatory components:

• Assessment 1
• Assessment 2

The programme includes different forms of assessment which allow for and promote students’ critical engagement. The assessment tasks may include an in-class assignment and/or a home-based written assignment using diverse assessment tools which may take the form of online and in-class discussions, examinations, case studies, reports, proposals, essays, and presentations, etc., as applicable to the diverse modules.