Master AI concepts and techniques to create intelligent systems.
Covers the basics of AI, its history, applications, and ethical considerations.
Explains how machine learning forms the foundation of AI, including supervised and unsupervised learning.
Covers the basics of NLP, text processing, sentiment analysis, and conversational AI.
Explores computer vision, image classification, and object detection using AI models.
Explains the development of expert systems and how knowledge is represented in AI.
Covers the integration of AI in robotics for autonomous decision-making and control.
Explains AI algorithms, search techniques, and optimization methods.
Covers the architecture and training of neural networks in AI applications.
Explores reinforcement learning concepts, policies, and rewards in AI.
Explains the applications of AI in healthcare, diagnosis, and medical research.
Discusses the role of AI in financial services, fraud detection, and trading.
Covers AI technologies used in self-driving cars and autonomous systems.
Discusses ethical concerns, fairness, and bias mitigation techniques in AI.
Explores the integration of AI with IoT devices for intelligent automation.