This includes deep learning, natural language processing, computer vision, reinforcement learning, and applications of AI in various domains such as healthcare, finance, and autonomous systems.
This course covers the theory and applications of artificial intelligence and machine learning techniques. Topics include supervised learning, unsupervised learning, reinforcement learning, neural networks, deep learning architectures, and their applications in various domains.
Introduction to Machine Learning
Linear Regression and Logistic Regression
Decision Trees and Ensemble Methods
Neural Networks and Deep Learning
Convolutional Neural Networks (CNNs) for Computer Vision
Recurrent Neural Networks (RNNs) for Natural Language Processing
Applications of Machine Learning in Healthcare/Finance/Autonomous Systems