Course overview
This course aims to equip students with a foundational understanding of machine learning concepts, their historical development, and their applications. By the end of the course, learners will be able to understand and implement basic machine learning algorithms and evaluate the algorithms on a variety of datasets using suitable evaluation metrics. This course prepares students to effectively apply machine learning techniques to real-world problems and sets the foundation for more advanced studies in machine learning and artificial intelligence.
- Deep Learning
- Neural Networks
- Transformer
Course learning outcomes
- Select a suitable neural network architecture for a given problem
- Implement neural network architectures in a modern framework
- Apply the machine learning pipeline to neural network models on complex datasets
- Evaluate different deep learning architectures for specific tasks
- Apply deep learning models for natural language processing and computer vision
- Present results and recommendations to stakeholders
Availability
Class details
Adelaide City Campus East
Class number 21666
Section PR01
Size 50
Available 41
Class number 21667
Section WS01
Size 50
Available 41
Class details
Adelaide City Campus East
Class number 40133
Section PR01
Size 30
Available 30
Class number 40134
Section WS01
Size 30
Available 30
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