|
Academic requirements :
Minimum Grade 12 with General math’s (2.00GPA)
|
Duration
1 Year Part Time (Saturday)
2 Semesters
|
|
Prerequsites :
Minimum 4 Years for Grade 12
Minimum 2 Years for Grade 12 + Cert IV/Diploma
|
Intake:
February & July
|
|
Award:
Advance Diploma PNGNQF Level 5
|
Delivery Mode:
Classroom & Online live
|
|
Technology requirements : Online Users
Specifically, students are expected to successfully participate in lectures, laboratories and projects using a portable computer (Laptop/Notebook/Desktop) with a substantial hardware configuration. Its minimal suitable configuration is 8GB of RAM (16GB are recommended); a modern 64-bit x86 multi-core processor (Intel i5 or superior); 250+ GB of available space in hard disk; WiFi card; and a recent version of Ubuntu, macOS, or Windows.
It is the responsibility of the student to ensure their laptop is functioning correctly and that they have full administrator rights to the machine. DLC cannot provide support to personal devices.
|
About This program:
This course aims to produce technically competent, innovative graduates that will become leading practitioners in the field of data analytics. Upon completion, graduates will be able to:
Conduct independent research and analysis in the field of data analytics
Demonstrate expert knowledge of data analysis and statistics, and the tools, techniques and technologies of data analytics utilized in both technical and business contexts
Critically assess and evaluate business and technical strategies for data analytics
Develop and implement effective business and technical solutions for data analytics
Critically appreciate ethical and data governance issues relevant to data analytics
The course is designed to accommodate those with specific interests in data analytics, whether that may be of a more technically focused or a more business focused nature. All learners will also gain exposure to pertinent legal issues and ethical issues associated with the data analytics field.
Students will gain exposure to product commercialization issues associated with data analytics. The course is delivered by faculty and practitioners using academic research, industry defined practical problems, and case studies
Subjects:
|
MS Business Skills
|
|
|
Data Analysis and Visualization with Microsoft Excel
|
Bi with Tableau
|
|
Data Analysis with Power Pivot
|
Microsoft Power Bi
|
