This course provides an advanced and applied exploration of machine learning techniques, focusing on real-world problem solving through data-driven approaches. Students will develop competencies in data preprocessing, deep learning architectures, and specialized applications in text and image analysis. Through hands-on implementation using tools such as PyTorch and interactive artifacts, learners will design, train, evaluate, and optimize machine learning models.
The course also introduces emerging paradigms such as Agentic AI, emphasizing ethical considerations, system reliability, and the strategic use of AI in complex domains. The learning experience integrates theory, practice, and critical analysis to prepare students for high-level professional and research applications.
- Teacher: Arpan Mahara