| DAC703 Machine Learning | |
| Campus: | Australian Technology Park, Eveleigh, NSW 2015 |
| Units of Credit: | 6 |
| Prerequisite or Corequisite: | DAC604 Coding for Data analytics and (DAC700 Applied statistics, or DC601 Computer system and networking) |
| EFTSL*: | 0.125 |
| Indicative Contact Hours per Week: | 3 |
| Tuition Fee | See Tuition Fee Schedule |
| Application Date: | See Key Dates |
| Unit Overview: | |
| The machine learning unit evaluates the practical uses and applications of machine learning in different areas. It introduces machine learning principles as well as the concepts of statistical learning and neural network learning. Applying practical cases from a variety of industries in the real world, the unit covers the types of systems used in machine learning applications and their underlying functions and specifications. It covers the training and learning process in machine learning algorithms as well as the applications of knowledge intensive learning. Furthermore, techniques for information retrieval and web navigation for data mining are evaluated. Feature extraction and classification, and theories and models for plausible reasoning are interpreted. The unit also covers computational learning theory, cognitive modelling and hybrid learning algorithms in order to develop an understanding of a vast array of machine learning applications in different areas. | |
*EFTSL = Equivalent full-time study load
