| Unit code & Title | ANA105 - Data Analytics with R |
| Pre-requisite | Not Applicable |
| Delivery modes | On-campus; Online; |
| Credit points | 10 |
| Study commitment | Average of 150 hours of teaching, learning and assessment over the trimester. |
| Scheduled learning (On-campus) | 2 × 3 hours on-campus seminar and tutorial weekly (for block mode) |
| Scheduled learning (AIA Online) | Recorded contents + 2 × 3 hour online seminar and tutorial weekly |
| Learning Outcomes |
|
R is an open-source software environment for statistical computing, machine learning and data graphics which is widely used by statisticians, business analysts and data scientist. This unit aims to provide a practical introduction to the R programming language for beginners through numerous real-life data and case studies. Students will be able to perform essential analytics tasks in the R environment, including reading and writing data, exploring and manipulating data, analysing data with statistical tools, presenting and communicating data with a variety of graphics, and conducting fundamental linear regression analysis.
Fees and charges vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study and their study discipline, and your study load.
Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.
For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit Current student page
Refer to Academic Calendar
