Data Capture and Preparations (12122.1)
Please note these are the 2025 details for this unit
Available teaching periods | Delivery mode | Location |
---|---|---|
View teaching periods | On-Campus |
Bruce, Canberra |
EFTSL | Credit points | Faculty |
0.125 | 3 | Faculty Of Science And Technology |
Discipline | Study level | HECS Bands |
Academic Program Area - Technology | Level 3 - Undergraduate Advanced Unit | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
A core skill of a data scientist is to capture, extract and clean data. Real world data often come from various data sources, in various formats and are unorganised. This unit introduces students to the concepts and techniques a data scientist employs in the early stages of data analysis process. This unit will provide hands-on experience in capturing data from sensors, collecting data from public information as well as working with existing data sets using real-world examples. Such data may be temporal or spatial, ordinal or categorical, embedded in documents or files. Students will learn how to import and clean the data, which usually involves multiple, often complicated, steps to convert data from its raw format to a clean format that greatly facilitates the later stages of the data analysis. This is known as data wrangling.
1. Work with sensors for capturing data;
2. Choose and apply appropriate techniques for capturing data from existing sources;
3. Import data into R;
4. Convert data from one format to another one in R;
5. Employ suitable techniques for tidying data; and
6. Develop a sound understanding of text mining methods in R.
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
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - understand issues in their profession from the perspective of other cultures
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 - be self-aware
3. UC graduates are lifelong learners - evaluate and adopt new technology
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Learning outcomes
Upon successful completion of this unit, students will be able to:1. Work with sensors for capturing data;
2. Choose and apply appropriate techniques for capturing data from existing sources;
3. Import data into R;
4. Convert data from one format to another one in R;
5. Employ suitable techniques for tidying data; and
6. Develop a sound understanding of text mining methods in R.
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
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. UC graduates are global citizens - adopt an informed and balanced approach across professional and international boundaries
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - understand issues in their profession from the perspective of other cultures
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 - be self-aware
3. UC graduates are lifelong learners - evaluate and adopt new technology
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Prerequisites
11372 Introduction to Data ScienceCorequisites
None.Incompatible units
11520 Data Capture and Preparations GEquivalent units
None.Assumed knowledge
Working knowledge of discrete mathematics, algebra and numerical analysis.
Availability for enrolment in 2025 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 |
---|---|---|---|---|---|
2025 | Bruce, Canberra | Semester 1 | 03 February 2025 | On-Campus | Dr Raul Fernandez Rojas |
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.