Programming for Data Science
Credit Points 10
Legacy Code 301113
Coordinator Franco Ubaudi Opens in new window
Description The use of computers and computer programming for Data Science is fundamental to the discipline. This introductory unit will briefly cover the use of spreadsheet systems and then will consider programming in the statistical system "R" in detail. Other special purpose languages will also be touched on briefly including SQL (Structured Query Language).
School Computer, Data & Math Sciences
Discipline Statistics
Student Contribution Band HECS Band 2 10cp
Check your HECS Band contribution amount via the Fees page.
Level Postgraduate Coursework Level 7 subject
Learning Outcomes
- Use Excel to manage and manipulate data.
- Extract, transform and load data using R and R-Studio; including reading and writing data files.
- Create complex R programs to conduct Data Science tasks.
- Use basic SQL to access databases.
- Apply simulation techniques to Data Science tasks.
- Create reports using Markdown and R-Markdown.
Subject Content
2. Introduction to R and R-Studio
3. Data Types, Variables , Expressions, and Data Structures
4. Input and Output
5. Control Structures: Loops, ,Conditional Expressions, and Functions
6. Simulation techniques
7. Object-oriented programming in R
8. Introduction to SQL
9. Using Markdown for reporting
Assessment
The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.
| Item | Length | Percent | Threshold | Individual/Group Task |
|---|---|---|---|---|
| Online Quizzes | 5 x 30 minutes | 20 | N | Individual |
| Computer Test | Lab based 1 hour practical | 40 | N | Individual |
| Assignment | 3,000 words | 40 | N | Individual |
Teaching Periods