ADS3001 - Advanced data challenges

Overview

This is the final in a series of Data Challenges units which draws together your mathematical, computational and applied studies, and builds on the industry-relevant data science case studies explored during the first two years of the Bachelor of Applied Data Science. You will apply this knowledge working in industry … For more content click the Read More button below. You will further develop and apply your analytic and technical skills to interrogate and understand large and complex real-world data sets drawn from academic, governmental and business problems. You will continue to develop your communication skills through a combination of written, oral and multimedia presentations, which communicate your analysis and conclusions to a range of potential stakeholders. Finally, you will work in teams to enhance your project management, collaborative and leadership skills. The placements will embed you in data science teams in a range of government, industry and academic settings. These placements will be complemented by weekly seminars to provide insight into real problems faced by experts in the field.

You will further develop and apply your analytic and technical skills to interrogate and understand large and complex real-world data sets drawn from academic, governmental and business problems. You will continue to develop your communication skills through a combination of written, oral and multimedia presentations, which communicate your analysis and conclusions to a range of potential stakeholders. Finally, you will work in teams to enhance your project management, collaborative and leadership skills.

The placements will embed you in data science teams in a range of government, industry and academic settings. These placements will be complemented by weekly seminars to provide insight into real problems faced by experts in the field.

Offerings

S2-01-CLAYTON-IMMERSIVE

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Dr Simon Clarke

Unit Coordinator(s)

Dr Simon Clarke

Learning outcomes

On successful completion of this unit, you should be able to:

Critically analyse data-oriented projects to break these down into achievable tasks;

Demonstrate the ability to work in a team to plan and complete a complex data-orientated project;

Analyse the ethical issues associated with data science decisions that arise;

Clearly communicate complex ideas to potential stakeholders using a variety of approaches;

Effectively manipulate, analyse and visualise data;

Implement a range of advanced machine learning algorithms;

Undertake independent research on data science techniques and relevant domain knowledge.

Teaching approach

Active learning

As this is the capstone unit for the Bachelor of Applied Data Science, the primary objective is to apply the learning from throughout the course and therefore the most appropriate learning method is active learning. This is achieved through the two forms of activity, placements and weekly seminars.

You will be embedded in organisational teams and undertake active learning. You will apply your accumulated knowledge to work in teams, plan and complete projects, interrogate large and complex datasets, implement advanced machine learning algorithms on the data, research new data science techniques to apply to your project, deal with any ethical issues associated with the data science decisions and communicate their results to a range of stakeholders through written and oral presentations (LO1-LO7). Furthermore, they will be exposed to a range of techniques and issues specific to their placement (e.g., LO2, LO3, LO4, LO7).

Assessment

1 - Assignments

2 - Reflective journal

3 - Supervisor report

Scheduled and non-scheduled teaching activities

Seminars

Workload requirements

Workload

Off campus attendance requirements