Overview

In today's data-driven business landscape, data engineering plays a vital role in enabling effective business analytics. This subject delves into the essential aspects of data engineering with a strong focus on the business context. You will explore fundamental concepts and techniques for data modeling, as well as cutting-edge frameworks and … For more content click the Read more button below.

Portfolio

Office of the Provost

Subject coordinator

Yuan Sun

Subject type

Undergraduate

Year level

Year Level 2 - UG

AQF level

Level 6 - Associate Degree

Available as elective

No

Available to study abroad / exchange students

Yes

Capstone subject

No

Academic progress review - Schedule A subject

No

Subject instances

To view instance specific details which include - Assessments, Class requirements and Subject instance coordinators - please select your preferred instance via the drop-down menu at the top right-hand side of this page.

Learning resources

Prescribed - Book - Python programming for data analysis

Career ready

Work based learning (placement):No

Graduate capabilities

COMMUNICATION - Digital Capability
DISCIPLINE KNOWLEDGE AND SKILLS
INQUIRY AND ANALYSIS - Creativity and Innovation
INQUIRY AND ANALYSIS - Critical Thinking and Problem Solving

Subject intended learning outcomes

On successful completion you will be able to:
1.
Build data engineering models in Python to derive valuable insights from real-world datasets.
2.
Evaluate machine learning techniques and utilise Python libraries to construct predictive models for business problems.
3.
Apply optimisation techniques to make data-driven decisions for solving real-world business challenges.

Learning activities

Enquiry-based learning, experiential learning activities