Exploratory Data Analysis and Visualisation G (11517.2)
Please note these are the 2024 details for this unit
Available teaching periods | Delivery mode | Location |
---|---|---|
View teaching periods | On-Campus Online |
Bruce, Canberra |
EFTSL | Credit points | Faculty |
0.125 | 3 | Faculty Of Science And Technology |
Discipline | Study level | HECS Bands |
Academic Program Area - Technology | Graduate Level | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
Data and its analysis and modelling underpin all aspects of work and society in the 21st century. This unit provides students with a thorough study exploratory data analysis and visualisation techniques. Exploratory Data Analysis is an approach to data analysis that employs a variety of techniques, mostly graphical. The main role of this approach is to open-mindedly explore the data. Visualisation enables the data to reveal its structural secrets and provide new insight into the data. Exploratory Data Analysis allows the data scientist to discover patterns, to spot anomalies, to test hypothesis and to check assumptions with the help of summary statistics and graphical representations. This unit will provide hands-on experience in data visualisation and summary statistics using real-world data examples.
This unit will be co-taught with 11374 Exploratory Data Analysis and Visualisation.
1. Detect missing values, outliers and other abnormal data prior to exploratory data analysis;
2. Identify the hidden underlying structures and patterns of the variables within the data;
3. Examine ideas and methods used in exploratory data analysis for real world applications; and
4. Demonstrate strong skills in using data visualisation techniques for analysis and communication of findings and results, along with statistical reporting.
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - take pride in their professional and personal integrity
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology
This unit will be co-taught with 11374 Exploratory Data Analysis and Visualisation.
Learning outcomes
After successful completion of this unit, students will be able to:1. Detect missing values, outliers and other abnormal data prior to exploratory data analysis;
2. Identify the hidden underlying structures and patterns of the variables within the data;
3. Examine ideas and methods used in exploratory data analysis for real world applications; and
4. Demonstrate strong skills in using data visualisation techniques for analysis and communication of findings and results, along with statistical reporting.
Graduate attributes
1. UC graduates are professional - communicate effectively1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - take pride in their professional and personal integrity
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology
Prerequisites
None.Corequisites
None.Incompatible units
11374 Exploratory Data Analysis and VisualisationEquivalent units
None.Assumed knowledge
Working knowledge of discrete mathematics, algebra and numerical analysis.
Availability for enrolment in 2024 is subject to change and may not be confirmed until closer to the teaching start date.
Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
---|---|---|---|---|---|
2024 | Bruce, Canberra | Semester 1 | 05 February 2024 | On-Campus | Dr Shuangzhe Liu |
2024 | Bruce, Canberra | Semester 1 | 05 February 2024 | Online | Dr Shuangzhe Liu |
The information provided should be used as a guide only. Timetables may not be finalised until week 2 of the teaching period and are subject to change. Search for the unit
timetable.