Course Description
The Bachelor of Analytics (Course CRICOS Code: 111123K) prepares students with the knowledge and skills to evaluate and apply different analytic tools to support decision making, including for organisational transformation. Students will have hands-on training in the use of different analytics tools, to optimize data assets, and to utilize predictive analytics to enhance business strategy and returns.
In this course, you will learn to gather and prepare data, extracting their meaning, to shape business strategy. You will gain skills in the use of analytical tools and techniques, to discover how data analytics can be applied in marketing, accounting, human resources management, logistics, manufacturing – just some examples of how business decisions can be disrupted by data-driven insights. For professionals looking to the future, now is the time to invest in learning the language of data.
AIA - SAS Joint Certification
Career Outcomes
- business analyst
- business intelligence specialist
- computer system analyst
- data analyst
- digital transformation consultant
- information analyst
- information manager/ officer
- market analyst
- predictive modeller
- business manager
Course Study Requirements
Assessment
Students learn through a variety of activities:
In-class discussions, case study analysis, business report writing, research work, practical problem solving, team building, role-play, debates and self-reflections. In the final year of the course, students will undertake a work integrated learning unit (120 hours of work placement), designed to be a capstone unit for the course.
Assessment types include case studies, projects, reports and presentations, problem solving, reflections and journals, tests and quizzes and a small number of examinations.
Admission and Entry Requirements
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International Students
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Domestic Students
Admission Criteria
Applicants with recent secondary school education (within the past two years). Note: If you do not meet the above criteria, then AIA considers successful completion of at least one unit of study in an accredited higher education program. Further details are available in our Admissions and Enrolment Policy and Procedures and English Language Proficiency Policy. Admission criteria can be satisfied through overseas issued qualifications which are deemed equivalent to accredited qualifications issued in Australia.Entry Requirement
| Study pre-requisite | Studies equivalent to Victorian Certificate of Education (VCE) units 3 and 4 with a study score of at least 30 in English (EAL) or at least 25 in English other than EAL and units 3 and 4 with a study score of at least 20 in one of Mathematical Methods or Specialist Mathematics. |
| Marks in final year of secondary school education | Equivalent to ATAR 60 (minimum). (refer to ATAR Calculations for more information) (Click to view ATAR Score Equivalency by Country) |
| Rankings and Adjustments | Entry to this program is competitive. Eligible applicants are ranked and selected in order of merit based on their academic achievement plus any adjustment factors, including Educational Access Scheme and/or subject adjustments. We will consider your entire academic record to determine your eligibility for entry. The highest level of education you have previously completed will usually determine how you are ranked. |
| Credit and Recognition of Prior Learning | Credit, recognition of prior learning, professional experience and accreditation from a professional body can reduce the duration of our study by acknowledging your earlier, relevant experience. |
| English Language Requirements | English proficiency can be demonstrated by an English proficiency test. Minimum requirement is IELTS 6.0 with no band less than 5.5 or equivalent. (Click to understand other accepted forms of English testing) |
These requirements are applicable to you if you are a Domestic student. This means you are an Australian or New Zealand citizen or an Australian permanent resident.
Admission Criteria
Applicants with recent secondary school education (within the past two years).
Note: If you do not meet the above criteria, then AIA considers successful completion of at least one unit of study in an accredited higher education program or vocational education and training (VET) study.
Further details are available in our Admission and Enrolment Policy and Procedures and English Language Proficiency Policy.
Entry Requirements
| Study pre-requisite | Victorian Certificate of Education (VCE) units 3 and 4 with a study score of at least 30 in English (EAL) or at least 25 in English other than EAL and units 3 and 4 with a study score of at least 20 in one of Mathematical Methods or Specialist Mathematics. |
| ATAR | 60 (minimum). |
| Rankings and Adjustments | Entry to this program is competitive. Eligible applicants are ranked and selected in order of merit based on their academic achievement plus any adjustment factors, including Educational Access Scheme and/or subject adjustments. We will consider your entire academic record to determine your eligibility for entry. The highest level of education you have previously completed will usually determine how you are ranked. |
| Credit and Recognition of Prior Learning | Credit, recognition of prior learning, professional experience and accreditation from a professional body can reduce the duration of our study by acknowledging your earlier, relevant experience. |
| English Language Requirements | English proficiency can be demonstrated by prior study in English. |
Special Consideration
Applicants will be considered for admission based on special consideration or disadvantage who can demonstrate ability to undertake study at the required level.
Course Learning Outcomes
On successful completion of this program, students will be able to:
- Select and apply the most appropriate data modelling tools to review, critically analyse and translate big data into business intelligence, drawing on their broad understanding of the context.
- Demonstrate an in-depth understanding of the role of data analytics in systems thinking to inform complex business decisions.
- Engage effectively and professionally in a workplace, demonstrating the ability to (a) collaborate within a team, (b) communicate clearly, coherently and independently.
- Demonstrate innovation and creativity, critical thinking, and professional judgement in analysing data to identify and solve problems.
- Engage with complex business scenarios to examine the professional and ethical implications in areas including privacy, data management, and the use of machine learning to inform business decisions.
- Demonstrate engagement in independent learning, maintaining currency and undertaking continuing professional development in their field.
Course Structure and Rules
| Title of program | Bachelor of Analytics |
|---|---|
| Structure of program | The program structure is based on three levels with the following details:
All units of study within this program are core. The program structure, with recommended study pathway is noted below. |
| Unit Code | Unit Title | Core or elective | Pre-requisite | Credit Points |
|---|---|---|---|---|
| BUS101 | The Macro-environment in Business | Core | – | 10 |
| ANA101 | Fundamentals of Business Statistics | Core | – | 10 |
| ANA102 | Tools for Data Exploration | Core | – | 10 |
| WIL102 | Work Integrated Learning (Foundations) | Core | – | 10 |
| BUS102 | Fundamentals of Management | Core | – | 10 |
| ANA103 | Data Analytics Fundamentals | Core | – | 10 |
| ANA104 | Databases for Business Intelligence | Core | – | 10 |
| ANA105 | Data Analytics with R | Core | – | 10 |
| BUS103 | Strategic Management | Core | – | 10 |
| Unit Code | Unit Title | Core or elective | Pre-requisite | Credit Points |
|---|---|---|---|---|
| BUS201 | Disruption and the Fourth Industrial Revolution | Core | – | 10 |
| ANA201 | Statistical Applications in Data Science | Core | ANA101 | 10 |
| ANA202 | Visual Analytics | Core | ANA101, ANA102 | 10 |
| BUS205 | Digital Ethics | Core | – | 10 |
| BUS203 | Project Management | Core | – | 10 |
| ANA203 | Data Wrangling and Analysis with Python | Core | ANA101, ANA103 | 10 |
| ANA204 | Predictive Analytics | Core | ANA101, ANA103 | 10 |
| EP201 | ePortfolio A | Core | – | 10 |
| Unit Code | Unit Title | Core or elective | Pre-requisite | Credit Points |
|---|---|---|---|---|
| BUS304 | Communication and Data Storytelling | Core | ANA202 | 10 |
| ANA301 | Social Media Analytics | Core | ANA103 | 10 |
| ANA303 | Analytics Project 1 | Core | ANA101, ANA105, ANA202, ANA204 | 10 |
| ANA302 | Customer Analytics | Core | ANA103 | 10 |
| ANA304 | Analytics Project 2 | Core | ANA101, ANA105, ANA203, ANA204 | 10 |
| EP301 | ePortfolio B | Core | – | 10 |
| WIL302 | Work Integrated Learning (CAPSTONE UNIT) | Core | All Level 100 and 200 units | 10 |
Materials and Resource Requirements
To undertake the Bachelor of Analytics, students will need to have:
A laptop computer, with following minimum requirements:
- Processor: Intel Core i5 or equivalent
- RAM: 16 GByte
- Storage: 1 TByte
- Graphics Card Memory: 2 GByte
Further information about computing requirements can be found in the Student Orientation materials and Bachelor of Analytics Handbook.
