DAS711 – Advanced Unsupervised Learning Techniques
About Course
- This course focuses on advanced methods in unsupervised learning, including clustering, dimensionality reduction, and anomaly detection.
- It emphasizes the application of these techniques to complex, high-dimensional datasets that do not have labeled outcomes.
- Students will explore theoretical foundations and practical implementations, gaining skills in the use of unsupervised learning algorithms to solve real-world problems.
Course Content
Week 1: Introduction to Unsupervised Learning
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Introduction to Unsupervised Learning
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LO1: Define key concepts and challenges in unsupervised learning
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LO2: Explain the role and importance of unsupervised learning in data analysis
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LO3: Summarize the fundamental differences between supervised and unsupervised learning
