Introduction to Artificial Intelligence (AI) Course

Objectives

• Understand the foundational concepts of artificial intelligence, including its definition, scope, and applications in various industries.
• Learn the basics of machine learning, including supervised and unsupervised learning, and understand how algorithms can automatically learn from data to make predictions or decisions.
• Explore different types of artificial neural networks, such as feedforward neural networks and convolutional neural networks, and understand their architecture and functioning.
• Gain familiarity with natural language processing (NLP) techniques and understand how AI can be used to process and understand human language.
• Learn about the principles of reinforcement learning and understand how AI agents can learn through trial and error and make optimal decisions.
• Understand the ethical considerations and challenges associated with AI, including bias, fairness, and privacy, and explore approaches to address these concerns.
• Gain hands-on experience by implementing basic AI algorithms using popular libraries and frameworks such as scikit-learn or TensorFlow.
• Learn about real-world applications of AI, such as image recognition, speech recognition, chatbots, and autonomous vehicles, to understand how AI is transforming various industries.