Introduction to AI
Artificial Intelligence (AI) encompasses the design of machines that mimic human cognitive functions such as learning and problem-solving. Unlike traditional robots that follow fixed instructions, AI systems adapt and self-correct through various learning processes, including supervised, unsupervised, and reinforcement learning. The rapid advancement of AI is reshaping multiple industries, raising potential concerns about job automation and ethical considerations while offering promising benefits in healthcare, education, and transportation.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- AI is distinct from traditional robotics in its ability to adapt and learn through experience.
- Machine learning includes supervised, unsupervised, and reinforcement learning methodologies.
- AI has significant applications in various fields, including healthcare, cybersecurity, and transportation.
Key Concepts
- -- Artificial Intelligence
- A computing concept that enables machines to perform tasks that typically require human intelligence, such as problem-solving and learning.
- -- Machine Learning
- A subfield of AI that focuses on the development of algorithms that allow computers to learn from and make predictions based on data.
- -- Deep Learning
- A subset of machine learning that simulates the neural networks in the human brain to process large amounts of data for advanced recognition and prediction tasks.
- -- Reinforcement Learning
- A type of machine learning where an agent learns to make decisions by receiving rewards or penalties based on its actions.
Additional Learning Materials
Supplementary resources to enhance your learning experience.